This made some waves. It was syndicated or summarized by outlets like Search Engine Land, which spurred more articles from smaller brands like this agency who straight up called this a “black hat SEO” tactic (eye roll).

We also heard about it directly from clients who sent us the article or told us other advisors told them these product category list posts weren’t helping. 

We saw Lily’s article when it came out and discussed it in depth internally. Lily Ray is a well-respected voice in the SEO community, including us, but in this case, our evidence strongly suggests her takeaway is wrong.

Across dozens of clients and hundreds of articles, we see no evidence of Google cracking down on self-promotional listicles. We also think the evidence in her article itself doesn’t support this thesis, as we explain below. 

What we think is actually happening is simpler: Google is cracking down on bad content. AI slop or human slop. Bad content absolutely hurts your SEO long term, whether it comes in the form of self-promotional listicles or anything else. And frankly, this isn’t new. It’s been true for decades.

In our client data, we’re seeing self-promotional listicles be just as effective now as they were years ago when we first started talking about the importance of this kind of bottom-of-funnel content. The key is that, like all content, they need to be written well. They need to be honest, and they need to be specific and detailed enough to be genuinely useful. 

We discuss all of this with data and examples below. 

Issue #1: Product List Posts Don’t Have to Be ‘Self-Promotional Listicles’

Before we get into the data, there’s an important detail that dictates whether your category list post is a misleading “self-promotional listicle” or not: force ranking your list and calling yourself the best. 

This is how Lily defines a “self-promotional listicle”:  “ranking the best companies or products in their niche and placing themselves in the #1 spot. The common thread is that the company publishing the blog post ranks themselves, and/or their own products, in the top position.”

Even worse is if you then pretend like the list is based on some objective analysis where you evaluated all the options and ended up “objectively” concluding your product is the best. 

We absolutely agree with Lily that this type of content is misleading. It’s also unnecessary.  

We routinely get all the benefits of ranking for these valuable “best X software” type keywords without positioning our clients’ articles as a ranked list of the best products. Searchers of these keywords are just looking for a list of good options, with clear explanations of which product is good for which situations. That doesn’t need to come with a ranking. 

In fact, we think not force ranking your list better fits the search intent of these keywords because not every product is good for all situations. You don’t know the specifics of every reader’s situation, so it’s presumptuous to call any product “the best”.

Discussing Your Product First Doesn’t Have to Mean Saying It’s The Best

Now, as a marketer, you should discuss your product first, simply because eyeballs drop the further down the page you go. You’re just giving yourself less exposure if you put yourself last. 

But as our examples below show, you can do that honestly and transparently. Many of our introductions include some version of “We’ll start with a deep dive into our own product and how we designed it to fulfill the criteria above.”

That’s simply telling the reader: “We’re proud of our product. Here are the choices we made when building it, who it’s a fit for, and why. And if it’s not right for you, here are other major players in the space.” What’s misleading about that? 

We’ve ranked for hundreds (maybe even a thousand or more) keywords like this over the years for 100+ clients. We never position them as force-ranked lists, and our articles rank for the keywords and convert extremely well (examples below).

Issue #2: There’s No Evidence That List Posts Are Being Dinged by Google

The core evidence in Lily’s article for a possible Google “crackdown” on list posts is showing declining traffic graphs of SaaS company blogs and noting that those blogs happen to have hundreds of “self-promotional listicles”.

But the self-promotional listicles only make up a tiny fraction of the total content on those blogs. She never isolates and examines the rankings and traffic of just those listicles. 

Here’s a table summarizing the traffic decline, but importantly, the number of self-promotional listicles versus total posts of every example in her article: 

Look at the last column. In all of the examples, the self-promotional listicles make up less than 10% of the total posts; for most, less than 5%. For some, less than 1%. So if the overall blog traffic is declining, how do we know it’s because of these listicles? 

We don’t.

To Lily’s credit, she never directly says any of this data proves anything is wrong with self-promotional listicles. It’s just insinuated. But the insinuation is strong. 

I mean, just look at the title and subtitle:

It’s not ambiguous what this is implying.

And as I mentioned in the intro, even though her post is implying and not proving, it got picked up by a bunch of other outlets. Many of those outlets went further than her to conclude outrageous things like saying these listicles are “black hat SEO”. The insinuation is strong enough to get people to jump to that conclusion. That matters because people will start changing their marketing strategy based on these insinuations. 

So what data would we need to see to really prove this? 

Well, to start, if Google is indeed cracking down on self-promotional listicles, you should see a decline in their rankings. Otherwise, what does a “crackdown” by Google even mean if those pieces aren’t being pushed down or off the SERP? 

We have that data from dozens of clients, and we’re simply not seeing any kind of widespread rankings hit on these articles. We’ll show a few examples to illustrate.

Our Data: Multiple Examples of Self-Promotional Listicles Doing Just Fine

Here are multiple examples of actual rankings of product category list posts from many of our clients. The data is from Ahrefs rank tracker, which we use internally. It’s never perfect, but directionally good enough. I’m showing a graph of the ranking position over the past year or so, including the late Jan 2026 period where Lily is saying all of the declines in her examples occurred. 

B2B tour operator software

This one has been ranking number one since the spring of 2025. You can see that over the course of a year, it’s been sitting at #1 almost the entire time. 

It’s also performing well on AI visibility, being cited and getting our client a brand mention for various variations of that term: 

Trucking management software

Also published in the spring of last year (about a year before I’m writing this) and after the first month, it consistently hovered in the top 10 for the entire year. No signs of any cracking down. 

Retainer management software

Steady for Nov 2025 to now. Not a sign of a dip in late January 2026. If anything, it seemed to move up a couple of spots then. 

AQM software 

Totally steady. I included this to show an example of natural ranking fluctuation, which you can see in April 2026 here. Google briefly removes the blog post, but after a few weeks, it moves right back to its #1 spot. This is normal fluctuation. 

Best private school for autism

Here’s a non-SaaS example. Also a natural ranking fluctuation in October 2025, but it goes right back to #1. No sign of any crackdown in late January. 

Best concussion clinics

Here’s one in healthcare, a field where Google is notoriously strict. This one has a bunch of other URLs Google tests for this keyword, and an entire month in Oct 2025 where the blog post fell off the SERP. But once again, it came right back. No late January dip. 

There are more…

These are just a few examples. We have tons of others. We debated how to show this data and whether we needed some large statistical analysis of hundreds of these posts in case people wondered if we cherry-picked the few that happened to maintain their rankings. We ultimately decided it wasn’t worth the effort or the downside of exposing a massive amount of client content strategy just to prove the point.

We think these six examples across different industries are enough to show that no widespread crackdown on these types of posts appears to be happening. You can absolutely still achieve strong, stable rankings for valuable category keywords without seeing signs of decline.

If you don’t trust our data, that’s fine; we urge you to just look at your own. Either you’ve never published product category list posts, in which case, why are you even reading this far? Or you have, which means you can look at your own rankings; you don’t have to trust us. 

What If It’s Just AI-Generated Content That’s Getting Dinged?

One of the most notable parts of Lily’s article is at the end, when she notes a couple of other common characteristics of the blogs she examined. One key pattern is that she ran them through an AI writing detector, and it said all had a 100% confidence that the text was AI-generated.

That’s a massive red flag. Folks have published studies showing ample evidence that Google is cracking down hard on sites with a heavy amount of low-quality AI-generated text. 

That alone could explain the blog-wide traffic declines in her examples. 

But I also want to highlight qualitative differences in writing quality between her examples and the posts we write for clients. This could also be hurting long-term ranking ability, whether or not a human or AI wrote them. 

Most ‘Self-Promotional Listicles’ Are Just Bad Writing (Examples)

Lily shares a few examples of specific posts in her article, which show clear examples of how not to write these bottom-of-funnel product category posts. 

First, there’s a post on top-rated test management tools. 

Look at the opening sentence: 

This is corporate marketing gobbledegook that doesn’t say anything useful. It also has questionable claims and unnecessary insertions of “2025”:

• No evidence or reasoning is given to support the claim that software delivery cycles started accelerating in 2025. It’s almost certainly not true. 
• In fact, test management tools have been a thing for a long time. Why are we even talking about 2025?
• Is “software delivery cycles accelerating” really the reason people need these tools? Software testing tools have been around for decades. 

The first two H2s continue this largely non-informative, corporate jargon writing:

Issues: 

• No one Googling “top test management tools” needs to be told what they are.
• Even more inane is asking “Why use them?” The searcher is already looking for them; they know why they’ll use them. 
• Once again, nothing magical happened in 2025. They’re just blatantly forcing the date into it because someone must have told them “it helps SEO”.
• So much corporate jargon: “organizations are adopting…to meet growing demands.” No one talks like this. 

This “Key Features” section is similar to something we’ve included in our bottom-of-funnel pieces for a long time: help the reader understand what they should look for when evaluating options.

But the above list is not useful. The descriptions are too short and generic. You can contrast this with how we do it in our examples below. 

Overall, this is just bad content, and bad content hurting your SEO long term is a tale as old as time.

This kind of writing exists throughout the examples Lily shares in her post. We won’t critique all of them. You can go find those articles if you want to read more. 

Our Examples: How We Write These Bottom-of-Funnel List Posts

Here’s an example of one of our bottom-of-funnel list posts, in this case targeting the keyword “trucking management software” (full article if you want to read it).

Here’s the full intro and the start of our client’s section:

A few important things to note in how we position this piece in the intro: 

1. We never say this is a ranked list
2. We never say Toro’s software is “the best” 
3. We never say we’ve “tested” all the others
4. We never allude to any sense that this is an objective third-party evaluation

Instead, we just describe what we know about the space (trucking management software, TMS) and steer the discussion to the needs of Toro’s target customer: bulk haulers, a subset of truckers. 

You can see this directness in the first H2. It doesn’t say “Toro is the best!” It says it’s software for bulk haulers, which is both true and notable. Most trucking management software is generic, so our discussion of what bulk haulers need is genuinely valuable to the reader. Their needs are different, and that discussion doesn’t exist online.

If you are a bulk hauler looking for a TMS, this is genuinely helpful content, even though it’s clearly selling Toro. 

See how the “self-promotion” isn’t, by itself, a negative? It’s if the company lies or pretends to be objective, or pretends they “tested” all the options, that it comes across as cringey (at best) or dishonest (at worst).  

In fact, for these bottom-of-funnel queries (like “trucking management software”), it’s our strong belief that the searcher is looking to be sold to. When you’re researching products, in particular complex or expensive options like many B2B purchases are, you want to understand the features, benefits, and differentiators of each option at a deep level. So if one of the brands has an article that basically lays out:

1. Here’s our view on what matters in this space
2. Here’s how we designed our product to align with that view 

That’s genuinely useful. It doesn’t matter that the content lives on the brand’s site. The reader knows where you are. They know the brand is selling their product, and that’s fine; they’re expecting a sales pitch and will use that pitch to help their decision-making. 

You can see this in action later in the piece when we introduce Toro:

We list what features you need as a bulk hauler, with real explanations, not just AI-sounding generic descriptions (see the second bullet as an example), and say how Toro meets those criteria. 

Then, throughout that section, we go into extreme detail about exact features and how they help bulk haulers:

This level of detail helps AI search in particular because AI recommendations rely on matching detailed pain points with solutions.

This is genuinely useful content for the target audience without any of the unnecessary pretending that you won some contest and ended up first.

We think content like this is aligned with Google’s long-term goals (provide truly valuable content to users for each keyword), and we’ve written content for these bottom-of-funnel category keywords in this way for 8+ years. All of them have survived countless Google updates.

And even though this piece isn’t a listicle, it wouldn’t feel complete without a little self-promotion. So if you want to talk about publishing honest, valuable content targeting high-converting keywords for your brand, you can reach out here. 

Traditional SEO is predictable. You pick a keyword, create content around it, build links, and over time, you rank. You know which keywords have volume. You know which pages rank. You can track exactly where you stand. It’s measurable and repeatable.

AI search is different. There’s uncertainty at every step. 

1. Prompts: You don’t know exactly what prompts users are entering, because users don’t type short, repeatable keywords. They have long conversations unique to them. 
   
2. Context: Even if you do know the prompts users are entering, you or your AI visibility tool isn’t going to get the same answer as a real user because LLMs factor in a massive amount of user history, memory, and context to generate a response that’s personalized to that specific person. (Read more: Invisible Prompts).
   
3. Repeatability: Even the same user, asking the same prompt repeatedly, will get different responses and citations each time.

So what do you do with all this uncertainty? How do you get those LLMs to recommend your brand and your product when users ask about solutions to their problems in your space? 

The answer relies on this key fact: LLMs still run on content. 

How Search Changes from SEO to AI Search

Here’s the key difference between traditional SEO and AI search.

In SEO, everyone searches with short keywords and largely sees the same results. Yes, some personalization is done based on your browsing history and location, but it’s mostly around the edges.

For example, say we both search for “project management software.” We’ll likely get similar results: 

Seems normal, right? 

But what if you’re at an enterprise company switching from Jira and you want something very specific, and I’m a small business owner currently using pen and paper looking for my first real project management tool? Those details absolutely affect what project management software makes sense for you versus me, but Google doesn’t have any idea. So it serves us the same ten blue links. 

The way we used to deal with this in SEO is going after a few longer tail variants when they exist, like “enterprise project management software” or “project management software for small business.” But even that is insufficient. That doesn’t capture the nuance I mentioned above: that you’re already on Jira and want something specific that Jira doesn’t offer, and that I’m looking for my very first project management software. 

Those are just two random examples. There are really an infinite number of possible specific requests and pain points for a customer looking for any solution. Traditional Google search simply didn’t have a good way of handling all this personal context. 

But AI search does. 

In AI search, each user has a unique, personal conversation with the LLM where they share a massive amount of context. The LLM understands their company size, existing tools, and highly specific pain points. This context comes from both the current thread and a large body of prior chat history, enabling the model to recommend products tailored to their exact situation.

Here is Benji asking Claude about the best project management software “for us.” Look at how Claude knows what our company is, how big, and more. Benji didn’t type any of that into that prompt, but it knows. We call this phenomenon Invisible Prompts. 

LLMs aren’t just surfacing articles from high-authority domains.

They understand what a user needs, search the web for relevant solutions, read those results, combine that with what they already know, and recommend the product or service that best fits the user’s specific pain points. 

That’s a fundamentally different dynamic. And it changes the kind of content you need to produce.

If you want LLMs to recommend your product, you need to give them the details they need to recommend you in the right scenarios. Not generic “what is project management” content. 

You need to publish specific content that covers:

• What types of customers your product is best for
• What specific use cases and scenarios it handles
• What pain points it solves and for whom
• The features that matter and when they matter
• The benefits and outcomes customers experience
• How you compare to competitors and what makes you different
• Case studies that prove you’ve delivered results

Introducing Your GEO Topic Map

Your GEO topic map is a collection of content that teaches LLMs everything they need to know about your product so they can recommend you in the right conversations.

Here’s how we build it for clients:

1. We map every product angle that matters. Your categories. Your competitors. Your use cases. Your target personas. The jobs your product does. The pain points it solves. This becomes your topic map: the full universe of conversations where an LLM could potentially recommend you. Most companies aren’t thinking this way, much less producing this content. 

2. We interview the people who know your customers best. We sit down with your sales team, your customer support team, your product team, your founders, all of the customer facing roles inside your organization. We ask them exactly what users are telling them are their pain points and use cases. Then we extract the specific positioning, features, and differentiators that make your product the right choice in each scenario. These details are not something you can get from Google research. AI generated copy will not by default produce this. The details required to produce this kind of content have to come from the people inside your company who talk to customers every day.

3. We produce content for each angle at the depth of a sales conversation, not an intro guide. There’s this long standing culture in content marketing where everything is written at an introductory level.  “Intro guide to this.” “Beginners guide to that.” That came from everyone chasing high volume SEO keywords that were by nature beginner-leaning. 

But beginner level content won’t help you when your customer asks advanced and specific questions to an LLM. It wants to recommend brands that talk at that customer’s level. So your content needs to meet the customer there. Think about the level of depth and detail that happens in a sales conversation: detailed discussion of features, screenshots, specific scenarios where your product applies, use cases, case studies. That’s how we write this content.

4. We target Google keywords if and when it makes sense. If some of the user pain points we uncover in our interviews with your team match a known Google search term, we’ll target those search terms with our content so you get two inbound channels (traditional search and AI search) in one go.

For most businesses, there are plenty of these product recommendation keywords (what we call bottom of funnel queries) on Google. Keywords like: “Best [category] software,” “[competitor] alternatives,” “how to [solve specific problem].” 

5. We produce case studies. LLMs are smart enough to connect the dots between a story of your product helping someone and their user who is asking them about a similar issue. So it’s our experience and belief that case studies help. They naturally have the elements of specificity and pain point/solution pair elaboration that we’re talking about here. 

6. We track your AI visibility at the topic level. To make this process work, you need to measure success the right way. That means tracking visibility at the topic level, not the individual prompt level. Unfortunately most AI visibility tools (like Peec, Profound, Scrunch) are default to measuring success on an individual prompt basis. But we built our tool, Traqer.ai to be consistent with this topic-based property of GEO. That’s how we track improvement in visibility for clients and ourselves: which topics are we visible in and how is that growing.

Case Study: Constitution Lending

Constitution Lending is a private lender competing against companies with 80+ domain authority, thousands of backlinks, and decades of industry presence.

We built their topic map by interviewing their lending experts, the people who talk to borrowers every day, and producing content covering every specific lending scenario their ideal customers face: LLC mortgages, DSCR loans for specific property types, bridge loans for particular situations.

The result: Constitution Lending now appears in AI search results for 50+ bottom-of-funnel prompts across ChatGPT, Perplexity, and Google AI Overviews — competing with and often outranking lenders that have been in the market for decades.

This didn’t happen because of an llms.txt file or restructured headings (these on-site hacks don’t help LLMs connect your brand to users’ pain points, read more why here). It happened because LLMs found detailed, specific content about Constitution Lending’s products and could match it to user queries.

[Read the full case study →]

Case Study: InnovationCast

InnovationCast makes innovation management software for enterprise companies. 

Innovation software has multiple use cases, from crowdsourcing ideas from a large employee base, to validating ideas, to scouting new technologies.

When we started working with them, they had a limited content and SEO presence. But by producing content in their various topic areas, we’ve built not only an SEO presence that generates qualified leads for them, but also AI visibility

For example, here is their topic based coverage for “innovation portfolio management software”:

And here it is for another, slightly different way customers talk about software like theirs: “technology scouting software”:

Next Steps

If you’d like to talk to us about building your brand’s topic-based GEO strategy, you can reach out here.

If you’d like to read more about our GEO experience, observations and research here is further reading that underpins this Topic-Based GEO approach: 

• Ultra-Specific Content: Why top-of-funnel content doesn’t matter for AI search and why ultra-specific content is necessary
• Prioritized GEO: Why on-page hacks like llms.txt don’t work and why content and web search is the foundation of GEO
• Invisible Prompts: Why you can’t see the full context behind users prompts 

If you’d like more articles like this as we write them, you can join our newsletter. 

Here’s an example: company leadership asks marketing, “How are we doing on GEO/AEO/AIO?” Marketing turns to a tool like Peec or Profound, which spits out a single brand-visibility percentage, usually shown in a graph. Marketing reports back to leadership, “We have 26% visibility!” 

If that number is higher than last week, everyone’s happy and thinks marketing is “doing their job.” If it’s lower than before, leadership assumes something is wrong and wants marketing to change what they’re doing.

Below, we argue that this approach doesn’t make sense because it’s fundamentally the wrong way to think about GEO performance. 

A brand’s “AI search visibility” isn’t a brand-level metric. It’s a function of the specific topics or prompts being measured.

Reporting visibility at the brand level—especially as a single percentage—is, at best, unhelpful and, at worst, outright misleading. 

As we explain below, this mindset can lead to several negative outcomes, including: 

• Manipulation of metrics to make GEO performance appear stronger than it actually is
• A focus on “ranking” for prompts that have little to no business value
• Marketing teams being disincentivized to push harder or pursue more ambitious GEO strategies
• Resources wasted on activities that have no real impact on lead generation or revenue

Visibility Happens at the Topic Level, Not the Brand Level

If you remove the AI visibility tools and their dashboards from the picture, the idea of a single “AI visibility score” falls apart. In the real world, no brand has one. 

AI search visibility isn’t like domain authority in SEO, which represents a real, meaningful concept: how much weight Google’s algorithm assigns to a domain when deciding what to rank. In SEO, a site with high domain authority will, on average, outrank a site with low domain authority, all else being equal. 

There’s no real-world equivalent to a single AI search visibility percentage. Brands have visibility—or don’t—within specific topics. And if a brand has strong visibility in one topic, that visibility isn’t correlated, based on any data we have seen to date, with its visibility in another. 

By its very nature, AI search visibility is a topic-specific concept. 

Topic Level Visibility Is Actionable

More practically, we believe viewing visibility at the topic-by-topic level is how marketing teams learn which actions actually improve AI search visibility. When teams rely on a single, overall visibility percentage instead, those details get buried and the signal becomes misleading.

Here’s a real example from one of our clients, Mirascope, which has strong visibility on the topic of “prompt engineering tools”:

By contrast, on the topic of “context engineering platform,” they have far less visibility:

What does averaging these two together tell the Mirascope team? Nothing useful.

Leadership should think about visibility in these two topic areas completely separately. The actions required to improve visibility for “context engineering platform”—publishing more content on the topic, clearly explaining how Mirascope supports context engineering, and conducting citation outreach on relevant articles—will have no impact on visibility for “prompt engineering tools.”

The SEO analogy applies here. If Mirascope ranked #1 for the keyword “prompt engineering tools” and #60 for “context engineering platform,” what use would it be to average the two and report on a blended rank? No one does this in SEO because it makes no sense. 

Yet this is exactly what happens in GEO, largely because popular AI search visibility tools default to showing a single, overall brand visibility percentage in their dashboards. 

Single Visibility Percentages Create the Wrong Incentives

A single AI visibility percentage often becomes misleading (at best) or downright manipulated (at worst).

Consider what happens when a marketing team starts tracking additional prompts—aspirational topics they aren’t yet visible for but want to be. Adding those prompts, by definition, drives the overall visibility percentage down. 

On the surface, it looks like AI search visibility declined. Leadership may even comment on it or assume marketing isn’t doing their job well. But nothing bad actually happened. Visibility across ChatGPT and other LLMs is exactly the same as it was the day before. The only change is that the team is tracking more topics and being more ambitious about its GEO goals.

Here’s a concrete example. On January 13, the visibility score in Peec for this brand was 26.7%: 

On January 14, we added two new prompts that were relevant to the brand but had no visibility. As a result, the visibility score dropped to 20%: 

In reality, the brand lost no visibility. The metric only looks worse because new prompts were added.

This creates terrible incentives. It encourages marketing teams to be less ambitious. Teams are incentivized to avoid tracking new prompts because doing so makes their visibility percentage look worse. 

That’s the exact opposite of good marketing. Teams should be encouraged to identify new, high-value topics they want to rank for—not discouraged from tracking them.

How Our Visibility Tool Traqer Solves This

This is exactly why we built Traqer to be topic-based.

Topic-level visibility sits front and center in our tool, and that’s how we report on GEO visibility to our clients.

This page is what marketing teams can share directly with executives or clients. At a glance, everyone sees visibility by topic and can quickly understand where their brand is performing well and where it isn’t.

In the Mirascope example above, it’s immediately clear that they perform well for “prompt engineering tools” but have work to do for “context engineering platform.” No one has to dig through reports or click elsewhere to find this information. 

Yes, Traqer also includes brand-level metrics at the top. But instead of collapsing everything into a single percentage, those metrics show the total number of topics where visibility is low, medium, or high. This distinction matters. Adding new topics doesn’t artificially reduce performance elsewhere. 

This approach does two important things:

• It aligns incentives correctly. You can add 10, 50, or 100 new topics or prompts without hurting your overall score.
• It keeps teams focused on what’s actionable: which topics already have strong visibility and which ones need work.

The Right Way to Think About GEO Visibility

Regardless of whether you use Traqer, another tool, or track visibility manually in a spreadsheet, our recommendation is to think about GEO visibility at the topic level. That’s the proper way to approach GEO strategy.

Overall brand visibility percentages are, in our opinion, a lazy way to assess GEO performance. They hide the details that should (1) guide your strategy and (2) show your team whether GEO efforts are actually working.

When you track topic-level visibility, you can:

• Identify which topics need immediate attention
• Allocate content creation resources to the right areas
• Measure progress on specific topics and initiatives
• Avoid false signals from percentage fluctuations
• Make data-driven decisions about where to focus your GEO efforts

It’s the difference between knowing you have “32% visibility” and knowing you dominate prompt engineering conversations but need work on context engineering topics.

One tells you nothing. The other tells you exactly where to focus next.

Further Reading

• You can read the full Prioritized GEO strategy we execute for clients.
• You can read more GEO strategy articles.
• You can check out Traqer for proper AI visibility tracking.
• You can reach out about working with us to improve your GEO.

While it’s great that customers are finding us and our clients through AI search, this creates the problem of reproducibility.  How do you get more of these leads if they’re coming from extremely unique and personal conversations with, say, ChatGPT?

You can’t see these “AI rankings” in your AI visibility software. Peec, Profound, or our tool, Traqer are not going to show you the three-page conversation your recent lead had with ChatGPT. No one has that data (besides OpenAI, who obviously hasn’t revealed it). These are private, highly personalized conversations where the AI tool knows an astonishing amount about the user’s pain points and needs. 

Company after company we talk to is saying they’re getting these leads, but they don’t know how. They don’t know exactly what customers are typing into LLMs, yet the leads keep coming.

We’re calling this phenomenon Invisible Prompts because you can’t see what they are. 

But they’re very real, and as I’ll argue below, they’re only going to grow. 

What Are Invisible Prompts? 

It’s important to clarify that by “Invisible Prompts,” we don’t just mean prompts of a slightly different wording that you happen to not be tracking — like “what are some good content agencies?” versus “find me the best content agencies”. 

It’s not as simple as just thinking of those alternative wordings and sticking them into your AI visibility tool, feeling like you have everything covered. 

This is not what we mean. It’s not a wording issue. It’s much deeper.

The issue is that even if a real user types in the exact wording you are tracking in some AI visibility tool, ChatGPT (or Claude or Gemini) will factor in a massive amount of heavily personalized information about your customer that you can’t predict. This extra personal information about the user will completely change what ChatGPT recommends to them. 

We’ve started thinking about this as the difference between the literal prompt and the effective prompt. The literal prompt is what the user literally types into ChatGPT. The effective prompt includes all the additional information ChatGPT knows about them. 

For example, one of our leads could type “find me a good content marketing agency”. What ChatGPT will actually do to generate an answer is take into account everything it knows about that customer — things like what size business they have, their budget, their industry, what they’ve tried in the past, who is on their team already, and more. 

So, although their literal prompt may just be “find me a good content agency”, their effective prompt is more like a 1000-word essay on their business situation that ends with “…and so taking all that into account, what do you think would be a good content marketing agency for me?”

This is fundamentally not trackable. At least not in the “SEO style” that marketers are used to, where prompts are like keywords, each with some search volume. 

What we’re saying is we are moving to a world where the search volume of most people’s prompts is one. 

Your AI tracking tool isn’t surfacing these prompts to you — even ones like Profound that claim to have data from millions of “real” chats. That data is coming from people who have volunteered (knowingly or unknowingly) to have their web browsing tracked. Tools like Profound summarize patterns in that data, and then say “these prompts” have “this many” searches. So, fundamentally, it’s still the old SEO way of thinking: there are keywords and those keywords have certain search volumes. 

What Profound or any other tool doesn’t know is the deep personalization underneath each prompt. 

That personalization is what’s deciding whether or not you are recommended to the user. 

Examples of Invisible Prompts 

Back in early 2025, Benji wrote about how AI search would reward ultra-specific, bottom-of-funnel content. That post was an early version of this argument: that LLMs would factor in all this personal context when making recommendations. 

In that post, he shared this example of one of our current clients who found us on ChatGPT. We asked her to share the chat where it recommended us. Here is her exact prompt and the beginning of ChatGPT’s answer, where it recommends us: 

Her literal prompt was just: “What are the best SEO companies in your opinion who have driven massive results with endless leads for people in our kind of space?”

But you can see from the response that the effective prompt was longer. Look at how ChatGPT knows her space, knows her goals, knows her constraints. She didn’t actually type that in. 

So here’s the issue: If we track this exact prompt in an AI visibility tool, we won’t see ourselves (Grow & Convert) mentioned, even though in real life, we were. 

I actually tested this. I opened an incognito ChatGPT window and typed in her prompt, and even replaced “our kind of space” with “the business loans and funding space” to help it along.

The response is totally different from hers and doesn’t mention us at all, much less as the top option: 

This is the visibility issue we’re talking about. 

The real prompt — with all the context, nuance, and detail shaping whether ChatGPT, Claude, Gemini, or any other AI recommends you — is far longer, more detailed, and more personalized than you will ever see.

It’s invisible. 

Why Invisible Prompts Are Only Going to Grow 

This phenomenon, from what we can tell, is only growing as AI tools become more and more ingrained in everyone’s personal and professional lives and workflows. More people are logging in and staying logged in (Do you know anyone who uses ChatGPT or Claude regularly but in incognito?). 

ChatGPT, Claude, and Gemini are building longer and longer histories of us. People are even using agents now and giving those agents access to their email and calendar. The context windows in these tools are growing (meaning they remember and factor in more information), and the tools themselves have memory features that remember things from all of your chats when answering new questions. 

In other words, ChatGPT knows more about a user who’s been chatting with it for a year than one who just signed up. That history is context. And context changes recommendations.

All of which means: the gap between the literal prompt and the effective prompt is only getting wider.

How to Get More Invisible Prompt Leads

So what do you do to get more AI search leads if the true prompts are invisible? That’s what every company who observed this asks us. 

Our answer is the same thing we’ve been saying since Benji’s AI search post last year: create ultra-specific content that teaches LLMs all the myriad use cases and pain points where your solution is a good fit. You need to feed LLMs the details they need to recommend you in specific scenarios even though you can’t predict the searches a priori. 

For example, we didn’t know our financial sector client above would ask ChatGPT for an SEO agency, much less how. We didn’t create content specifically for her prompt. We’ve just been writing about how most content marketing does an awful job of generating leads, and how we fix that, for 10 years. 

That’s what you need to do. Create content for as many specific use cases and scenarios as possible. Start with the places and ways you shine. Start with actual case studies. Then move to features, pain points you solve, and the specific situations where your product or service is the right fit.

This Is Why Owned Content is Tier 1 in Prioritized GEO

This is also exactly why we have “owned content” as the highest priority tier in our Prioritized GEO strategy. 

Creating a variety of your own content, as opposed to chasing mentions in Reddit, gives you the room to discuss all the nuance and detail of where and when you shine, what pain points you solve, and more. 

You can do this easily on your own site. On Reddit, what are you going to do? Drop your name in one sentence? That’s not enough context for an LLM to connect you to a specific user’s needs.

What Not to Do: Over-Focus on Single Prompt Visibility

It also explains why we de-emphasize Tier 3, the on-site content tweaks. Adding a schema or an LLMs.txt file won’t help you cover these unique scenarios. An FAQ might help at the margins, but what’s far more effective than that is actual detailed content.

It also means that trying to game the system and show up for a single really specific prompt doesn’t make sense, because no one is actually going to ask that exact prompt. If you produce a dedicated article for one narrow prompt and show up for it, it may look good inside AI visibility tracking software, so your client or management team might be happy. But possibly no one is going to have that exact exchange with an LLM, so it’s not likely to help in a real scenario.

How to Measure Progress  

So is measurement totally hopeless? No. This is all still evolving, but we don’t think so. We’re actually leaning heavily into Topic-Based GEO to solve this, and here’s why.

While you can’t know the exact prompts people will use, you can observe, across clients and over time, trends in how much you’re showing up in AI search at the topic level.

We can see that clients with established brands and years of rock-solid SEO presence in their industry have visibility numbers like this:

While clients that are much younger, with newer domains, and without a long history of content and SEO presence, have numbers like this:

That matters. 

And as per Topic-Based GEO, we can see this across topics. For example, our own AI visibility for “B2B content marketing services” versus “B2C content marketing services” looks completely different:

While we’ve had both B2B and B2C clients and our process works on both, we’ve had more B2B clients, have written more about B2B challenges, and published more B2B case studies. So the industry — and by extension, the LLMs — know us better in a B2B context, and that shows in visibility differences.

These topic-level differences are actionable. It means if we want to get more B2C clients, we need to start producing more content about our B2C work. That way, AI tools will have that information and context and be more likely to recommend us when someone who works at or owns a B2C business asks about content agencies.

That’s how you work invisible prompts in your favor. The prompts themselves may be invisible, but you can still monitor your presence when certain topics are broached.

Which takes me to a final analogy before we close.

Invisible Prompts Are Digital Word of Mouth

This is all curiously similar to the oldest and most effective marketing channel of all time: word of mouth. 

Word of mouth is the holy grail of marketing and brand building. You eventually want to just be recommended whenever someone asks for a product or service in your space. 

But think about what actually happens when you ask your friend for product recommendations. That conversation has all the nuance and detail about your specific situation behind it. 

For example, if I ask Benji for surfboard recommendations, my literal question to him may just be “Hey what board should I buy?” but in his head, he’s going to apply the same complexity that ChatGPT does. He’ll factor in all he knows about me and my surfing: the fact that I’m a beginner, that I’m 6’6” tall, that I currently ride a 10’ foam board, and that I’m extremely handsome. All of it matters. 

So while my literal question to him is short (“What board should I buy?”), the effective question he’s answering is much longer. It includes all the details he knows about my surfing. 

That’s true if someone asks a friend about buying software, hiring a law firm, buying clothes or shoes, or even finding a good coffee shop. 

AI search is similar. Just replace the friend or colleague who knows a lot about you with ChatGPT, Claude, or Gemini. 

The only difference: Benji knows about surfboards from years of actually surfing. ChatGPT only knows what it has read. So if you want LLMs to recommend to you the way a knowledgeable friend would, you need to have published the content that gives them the context to do it.

You can’t predict the invisible prompts. But you can build the content foundation that gives LLMs enough detail to recommend you when those conversations happen.

But this field is like the wild west right now. Every week a new tactic is hyped as the thing you “must do” to show up in LLMs: add llms.txt, add key takeaways to content, or word headings as questions.

People can’t even agree upon a name for this field:

• GEO: Generative Engine Optimization
• LLMO: LLM Optimization
• AEO: Answer Engine Optimization
• AIO: AI Optimization

…much less what the best practices are.

This endless stream of GEO tactics is confusing marketing teams. We see it in questions from our clients, emails we receive, and all over the web.

The real issue is misplaced priorities. People don’t know what to do first or how to move forward with limited budgets and time. They want to cut through the noise, focus on what actually works, and skip the tactics that are all hype or hearsay.

We’ve spent the last few months testing these tactics. We even built our own AI visibility tool, Traqer.ai, to help track clients’ AI visibility because existing tools had too many issues (a topic for another article).

While we don’t have all the answers — nobody does — what we do have are results. Our clients are consistently being mentioned, and our articles are cited in ChatGPT, Perplexity, and Google AI Overviews.

We’ve developed a framework to help clients consistently reproduce these results. We’re calling it Prioritized GEO because it organizes all the random GEO tactics you see online into clear tiers of priority.

This article introduces our Prioritized GEO framework, explains the reasoning behind it, and shares real client results from using it.

If you’re interested in working with us to grow your AI search visibility, you can learn more or reach out here.

The GEO Priorities Pyramid

The first step to prioritizing GEO tactics is categorizing them. Every tactic we’ve seen fits into one of three buckets:

1. Owned content
2. Off-site mentions
3. On-site tactics

Owned content is content you write and publish on your own site.

Off-site brand mentions are getting online publications like magazines, industry sites, or communities like Reddit or Wikipedia to mention you (“digital PR”).

On-site tactics is what we’re calling everything that involves changing your site or content to help LLMs better understand it, like adding llms.txt, starting articles with “key takeaways”, wording headings as questions, and more.

The prioritization of these three groups can be summarized in what we call our GEO Priorities Pyramid:

The bottom of the pyramid — Owned Content ranking in Google — should be prioritized first, as it’s the foundation of your GEO strategy. Then, off-site brand mentions serve as a way to further boost visibility. Finally, on-site tactics can be layered as the cherry on top, but they shouldn’t be relied on to produce outstanding GEO results on their own.

To understand why, we first need to explain how LLMs gather information to formulate responses, and how your brand can influence them.

How GEO Works

The Two Mechanisms Behind Every GEO Strategy

All GEO tactics operate through one of two mechanisms:

1. Exposing your brand to LLMs
2. Helping LLMs better understand your content

Owned content (the foundation) and off-site mentions (digital PR) both work by exposing your brands to LLMs, while on-site tactics are designed to help LLMs better understand your content once they reach your site.

We’ll start with the bottom two layers of the pyramid: owned content and off-site mentions. Namely, how they both rely on traditional web search to expose your brand to LLMs.

Why Web Search Is Foundational to AI Visibility

Most people don’t realize that both on-site content and off-site brand mentions boost AI visibility by surfacing your brand to LLMs.

Not only that, but they also do so with the same intermediary step: by showing up in traditional search results on Google or Bing. LLMs encounter your brand when they crawl or search the web to produce their answers.

This is a critical point worth emphasizing: GEO is fundamentally linked to traditional SEO because LLMs search the web to help produce most responses — in particular, responses about product recommendations, which are the responses most marketing teams should care about.

Yes, of course LLMs also draw from their training data to generate responses. But AI companies don’t reveal much about what goes into their training data or how often they update it, so it’s unclear how to influence training data.

What is clear is that these LLMs actively search the web to supplement their answers — a process called grounding — to ensure their answers are up-to-date and accurate.

OpenAI even notes on ChatGPT’s search help page that it performs searches whenever it believes an answer could benefit from one, not just when a user explicitly clicks “Search.”

ChatGPT doesn’t search the web every time, but when you ask for product recommendations, it usually does.

How can you tell when a response is grounded? There are two key clues.

First, ChatGPT will literally say “Searching the web…” or even show what it’s searching for:

Or, if a response includes citations, it means ChatGPT used web search to ground its answer:

Meanwhile, Google AI Overviews and Perplexity are literally web-search summarizers — they pull content from across the web and then summarize the results in their output.

Here’s Google AIO’s own explanation of how AI Overview works:

And here’s the same from Perplexity’s article on how it works:

So if we know that LLMs can be influenced through their web searches, the natural next question is: what keywords or prompts should a brand try to rank for?

Why Bottom-of-Funnel Topics Should Be Prioritized in GEO

Bottom-of-funnel topics should be your top focus in GEO because they:

1. Actually have a shot at getting your brand mentioned by LLMs.
2. Are far more likely to be grounded in web search.

Let’s break this down.

In traditional SEO, top-of-funnel keywords used to drive a lot of traffic. As we’ve stated for a decade, that traffic rarely converted, but at least it got traffic to your site.

But in GEO, top-of-funnel topics don’t drive traffic because users don’t need to leave the LLM to get answers to those questions.

When users ask ChatGPT for how-to advice or to learn about a topic, they typically stay within ChatGPT for the entire exchange. They don’t need to visit your site unless they really want to read your article — and that’s literally the point of these AI tools: they answer your questions so you don’t have to search the web yourself.

Yes, top-of-funnel queries may include sources (they can also be grounded in web search), but the click-through rate on those sources is extremely low.

Note: OpenAI doesn’t release click data for ChatGPT, but we can infer the trend from Google AIO data, which shows a huge reduction in organic search result clicks when AI Overviews are present.

In short, for top-of-funnel topics (like “what is” or introductory “how to” content), LLMs either provide an answer without citing sources or mentioning any brands (so you get zero traffic), or they cite sources but the traffic you get is minimal. Not a great strategy, so don’t prioritize top-of-funnel content for GEO.

Instead, focus your AI visibility efforts on showing up when users ask about products. These are “bottom-of-funnel” topics with prompts like “what are the best accounting tools for a small business?” or “Who are the top SaaS content marketing agencies?”

For these prompts, the LLMs will list brands or products in its response. Your goal is to be one of them (client examples below). No source click needed. It’s literally recommending your product to the user.

And to emphasize what we said above: for these product-related topics, LLMs are very likely to search the web to help supplement their response because they know that their training data isn’t likely to have the most up-to-date information on the best products in a particular space.

If your brand shows up (and is discussed positively) in these web searches, you have a shot at being recommended by LLMs.

To summarize:

• Prioritize bottom-of-funnel topics as they drive almost all of your GEO results (traffic and conversions).
• All major LLMs use web search to decide which products to recommend for those prompts.
• Showing up in traditional Google search is the key to your GEO strategy.

Prioritizing the Three Categories of GEO Strategy

1. Owned Content Is the Foundation

If both owned content and off-site brand mentions expose your brand to LLMs via web search, why do we have owned content as the foundation of the pyramid, with off-site PR tactics secondary? There are several reasons.

Owned Content Gives You Space to Control Your Brand Narrative

You have full control over the depth and direction of content on your site, giving you the space to tell your brand and product story. You can make your content extremely detailed, covering:

• Your features in detail
• The pain points you solve
• The customers that are ideal versus non-ideal
• Your differentiators versus competitors

This matters in AI search — especially with ChatGPT — because users don’t just type short keywords into these tools; they have conversations. ChatGPT looks for products that solve a user’s specific problem. It’s not just matching phrases or counting backlinks like traditional SEO.

To recommend you, it needs to understand exactly who your product helps, how it helps them, and why it works.

This is the long tail of GEO, where tools like ChatGPT recommend products and services through prompts and conversations so personalized to the user that no tracking or AI visibility tool can fully capture them.

We discuss this at length in this article.

Owned Content Kills Two Birds with One Stone (GEO + SEO)

SEO still works. I know it’s not cool to say right now but it’s the truth. It’s still driving way more traffic than ChatGPT, it’s the foundation of Google AI Overviews, and it’s driving leads month over month for our clients.

For example, here are the monthly free trial starts from people landing on G&C content for the past two years for one of our clients. This doesn’t even include conversions from AI mentions that the content influenced, it only reflects direct traffic from our articles:

So if we’re talking about prioritizing, you should focus on the thing that gives you two channels in one effort. Your own SEO content does that far better than a short mention on Reddit.

Less Algorithm Update Risk

If your GEO strategy relies heavily on showing up on one site (like Reddit), you run the risk of OpenAI, Anthropic, Google, or Perplexity tweaking their algorithms to rely on that site less — and killing your GEO strategy overnight.

In fact, that literally happened with Reddit on ChatGPT:

In September, multiple people reported that the number of prompts with Reddit as a source dropped dramatically. So if you’d spent thousands on “Reddit marketing’” before then, it very likely was wasted (or made much less effective).

But the chances of ChatGPT and others de-prioritizing all sites across the internet (like yours) is very low. Your brands’ site is one of billions that make up the bulk of the internet’s content. They have been used to power Google results for decades and aren’t easily “updated” away. We think there’s less “update risk” with your own content than relying on a single major outlet.

Easier to Execute

For most brands, producing your own content to rank on Google is both faster and cheaper than “digital PR.” Most companies, if pressed, could produce a blog post for each of their top three SEO keywords this month. They likely know who on their team would write it, how much it would cost, and what the final product should look like.

But if I asked you to get Reddit mentions or land a feature in a top industry publication right now, how would you do it? Most companies haven’t done that before. They don’t have the internal know-how or the right vendor relationships.

You might say “we’ll just hire a PR agency,” but have you done that before? Do you know how to vet them or tell if what they’re doing is actually working?

This kind of organizational know-how matters. It could take you a year to figure it out — a year you could have spent publishing and ranking for your key bottom-of-funnel terms while LLMs start discovering you.

That’s why we’re not saying digital PR is a bad strategy, just that it should come second on your priority list.

2. Off-Site Brand Mentions Help Boost Visibility

As we said, off-site mentions work through exactly the same mechanism as owned content: by getting you to show up on Google first.

This means Reddit, Wikipedia, and other supposedly “special” sites that help you get mentioned by LLMs really just boil down to showing up in traditional Google or Bing searches when LLMs search the web to formulate their responses.

Which leads to our #1 advice for this category: focus your attention on getting mentions in sites that actually appear for the queries and topics you care about, not just sites that people claim are the most cited by LLMs overall.

The Problem with “Where AI Gets Its Info” Charts

You’ve probably seen those LinkedIn posts with charts showing “Reddit is the most cited source by ChatGPT”.

The implied or sometimes explicitly stated takeaway from these studies is that brands should invest in Reddit marketing.

But it’s important to remember how these studies work. They’re just adding up citations across a bunch of queries that may or may not have anything to do with your brand.

For example, look at the footnote below the graph on the righthand side above:

“Based on 150 thousand citations from 5,000 randomly selected keywords from Semrush database.”

How do you know if those random keywords have anything to do with your brand or not? You don’t. What you should care about is what sites show up for the queries or prompts your brand is targeting.

We’re finding that for many of our clients (especially B2B clients), the most cited domains are industry publications, not Reddit or Wikipedia.

For example, take our client Toro TMS, which makes software for trucking and bulk hauling companies. Here are five prompts related to the topic “trucking management software”:

And here is Traqer.ai’s analysis of the most popular domains cited for each of these prompts across ChatGPT, Perplexity, and Google AI Overview:

The domains cited most are:

• PCS Software
• TruckingOffice
• Connecteam
• Wise Systems
• Toro TMS (our client’s domain)

All of these are trucking, transportation, or dispatching related sites. Not Reddit. Not Wikipedia.

We also see this pattern in less niche industries.

Here are the most cited domains across five prompts in the topic “best project management software” a very competitive, popular topic.

The prompts:

The most cited domains:

Again, all project management software domains. None are general community sites.

We have countless other examples like this across our client base. For these clients, it wouldn’t make sense to prioritize getting Reddit mentions.

Do Citation Outreach Instead of General “Reddit Marketing”

Instead, brands are better off doing citation outreach. This means identifying the domains and pages that actually get cited for your target queries, then reaching out and pitching why you deserve to be included in their lists or articles.

This will get your brand mentioned in the domains and pages that LLMs are actually finding and citing when generating their responses.

We offer this citation outreach as a service for clients in our engagements.

3. Why On-Site Tactics Are the Least Important to GEO

The third and final category of GEO tactics is what we call on-site tactics. These include things like:

• Adding an llms.txt file to help web crawlers better understand your site
• Including “key takeaways” at the top of each article to signal what it’s about
• Adding FAQs (on pages or site-wide) since LLMs tend to favor question-and-answer formats
• Changing your headings to questions for the same reason

Notice how these differ from the first two categories of GEO strategies. They don’t help your site get discovered by LLMs, they’re meant to help LLM crawlers interpret your site, brand, and products once they’ve already found you.

That’s why on-site tactics sit at the bottom of our Prioritized GEO framework.

Getting discovered by LLMs is far more important than helping them “understand” your content. If LLMs aren’t discovering your content when they’re generating answers, then what’s the point of any on-site optimization? That’s why LLM exposure is fundamentally more important than assisting LLMs in content understanding.

The entire magic of LLMs is that they already understand natural language. If they’re discovering your content and it’s written reasonably well, they’ll get it.

That said, should you try these on-site tactics? We’re testing them as we write this, but here’s what we know so far:

• llms.txt – This doesn’t seem to help at all. It’s just a proposed idea from Jeremy Howard, the developer and founder of fast.ai, about how sites could help LLMs crawl a site. There’s no evidence OpenAI or others use it, and our tests suggest it doesn’t make a difference. We don’t recommend spending time on this.
• Key takeaways, FAQs, etc. – We don’t have clear data on this yet but we are testing some of these tactics. What we have data on is that multiple clients are showing up on LLMs with our content that doesn’t have any of these tactics applied to it. So while we don’t have proof these don’t work, we have plenty of evidence (some below) that they aren’t necessary.

Process: How We Execute GEO for Clients

These are the steps we take in an engagement with clients to build and execute a content strategy that gets both GEO and traditional SEO results.

#1. Identify Bottom-of-Funnel Topics

Our process starts with topic ideation. Using our Pain Point SEO framework, we identify bottom-of-funnel topics an ideal customer might search when looking for a solution like our client’s.

Next, we find traditional SEO keywords that align with these topics.

For example, our client InnovationCast developed software for innovation departments in large companies to manage ideas and innovation workflows. Their most foundational bottom-of-funnel topic is “innovation management software”.

We then find traditional SEO keywords like these that both humans and LLMs might search when researching innovation management software:

Important note: If you rank in the top few spots for keywords like this, you’ll naturally capture a range of long-tail variations. We’ll show an example using these exact keywords below. This matters because LLMs may phrase their search for innovation management in many different ways — a concept known as “query fan-out”. Focus on ranking for the head term first, and the long-tail variations will follow.

#2. Produce High-Quality Owned Content as the Foundation

This content should be the foundation of your GEO strategy as per our GEO Priorities Pyramid. It should rank for the traditional SEO keywords that both humans and LLMs search when looking for products like yours.

So, it’s important and therefore needs to be written really well. Remember, LLMs will act like your SDRs (sales development reps) and summarize and pitch your product to their user via this content. Good content equals a good pitch.

It’s our firm belief that this foundational content shouldn’t be AI generated or written by a freelancer who doesn’t know your product (the flawed “Google research paper” approach).

To produce high quality sales-level content on these topics, we use our interview-based writing method to interview the most knowledgeable people in the organization on how the product should be positioned: sales, founders, product leaders, head of marketing, etc.

These pieces need to cover details of who the product is for, how it’s used, what pain points it solves, benefits, features, and more. That’s what gives you a chance at showing up at the extremely specific queries a customer might type into ChatGPT when asking for products.

If you still want AI assistance for writing, you can try our writing product Wave Writer — it learns your product’s positioning and brand arguments to produce far better content than other methods.

#3. Link Building and/or Citation Outreach (Optional)

After content is published, we do traditional link building to earn backlinks from contextually relevant domains.

We use our AI visibility tool Traqer.ai, to identify which domains are most frequently cited for prompts related to the topic. Optionally, we run a citation outreach campaign to contact those sites and ask if they’re willing to include our client’s product in their list.

#4. On-Site Tactics (Optional)

Finally, after you have the foundational content written, you can also test or just use some of these on-site tactics like key takeaways or FAQs. Our current client results don’t indicate that these make much of a difference in AI visibility but they also seem harmless if you want to include them.

Our rule: Don’t let these GEO tactics get in the way of creating high-quality content that impresses real customers and drives conversions.

Results: AI Visibility Examples From Our Clients

InnovationCast: Enterprise B2B SaaS

Here are results from the example around innovation management software above.

Traditional SEO Rankings

Our piece on innovation management software is ranking for these traditional SEO queries:

You can see how it’s ranking in the top spots for a variety of traditional SEO keywords related to innovation management software. This is the natural “query fan out” that foundational SEO content results in. This helps give you visibility on a bunch of related searches LLMs may perform when generating a response.

Then we monitor visibility using Traqer on ChatGPT, Perplexity, and Google AIO:

You can see in the Traqer screenshots how different prompt phrasing gives you very different visibility results.

This is why we track multiple related prompts for a topic, not just one.

Constitution Lending: Evidence of ChatGPT Directly Using Our Article’s Wording

Our client Constitution Lending is a private lender for real estate investors (e.g., folks flipping houses). One of their main loan types is “DSCR loans.” Their differentiator is fast closings and high loan-to-value (LTV) ratios, which we write into every article we produce for them.

When we ask for fast-closing, high-LTV DSCR lenders in the US, it recommends Constitution Lending:

But not only does it mention them and cites our article on DSCR lenders, but it cites the exact value props and features we state in that article — like loans up to 80% LTV, quick pre-approval letters, and closings in as little as four days:

This is why it’s important that this foundational GEO content is carefully written. How you position your product in this content is how ChatGPT and others will position it to their users.

Google AI Overview

We’ve also seen plenty of cases of this in Google AI overviews. Here, it names our client Insider as one of the best CDPs (customer data platforms):

It cites and links to the article we published on their site about the best CDPs.

In fact, clicking the link doesn’t just open the page — it scrolls down and highlights the section where we discuss the 5 best enterprise CDPs, naming Insider first and discussing their platform in great detail:

Perplexity

Here’s a jobs to be done (JTBD) query packed with serious buying intent and laser-focused specificity:

I have a business in the healthcare space that I’m looking to sell. Can you help me think through what I need to do to sell it?

Our article for Axial — a company that helps business owners looking to sell find a broker — appears as the first source on Perplexity:

Notably, this article ranks #1 on Google for “how to sell my healthcare business.”

Want to explore executing this strategy for your brand? Reach out to us.

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During that time, particularly in the last two years, we’ve also seen the SEO landscape shift significantly. AI Overviews now appear for a large percentage of searches, zero-click searches continue to rise, and the top of the funnel content strategies that once drove traffic are producing diminishing returns for many companies.

These changes have made it even more critical to focus SEO efforts on the right keywords and the right content approach. And yet, through speaking with many different software companies who’ve done SEO previously (either in-house or through an agency), we’ve learned that companies and SaaS marketers often struggle to achieve the SEO results they’re seeking. 

Specifically:

• They focus too heavily on top of the funnel, high-volume keywords that drive traffic but rarely convert (an approach that’s become even less effective as AI engines absorb informational queries).
• Their feature and solutions pages often don’t end up ranking for their intended keywords.
• They don’t see meaningful increases in trials, demos, and product signups as a result of their SEO efforts.

In our opinion, these are strategy problems, not issues at the tactical level (e.g. fixing broken links or doing on-page SEO). To fix these problems, you need to fix your SEO strategy. 

In this article, we explain why these problems are so common among B2B SaaS businesses that try to do SEO. And then we walk through a 5-step process that you can follow to create a SaaS SEO strategy that solves these problems, based on the process we use at our agency.

The 5-step process we’ll cover includes:

1. Identifying high-intent keywords: Prioritize finding keywords with high buying-intent, that is, those that indicate people searching are looking to buy or solve a problem your product solves — instead of only prioritizing search volume.
   
2. Producing a unique piece of content to rank for each keyword: Create dedicated pages or blog posts for each keyword that deeply satisfies search intent instead of simply sprinkling SEO keywords throughout a bunch of blog posts.
   
3. Selling your product through your content: Talk about your product extensively in these articles including outlining your unique product features and differentiators. Don’t worry about common content marketing myths about not selling your product.
   
4. Technical SEO: Fix and monitor for technical SEO errors.
   
5. External link building: Generate backlinks to boost domain authority and keyword rankings.

Curious about having us do SEO for your business? You can learn more here. Or, if you’d like to learn the SaaS SEO strategy that we share below, we also teach our content marketing strategy and process in our course and community.

How Most Businesses and Agencies Approach B2B SaaS SEO Strategy 

As we mentioned above, we’ve spoken to many B2B SaaS companies about their past experiences doing SEO. And through those conversations, as well as what we see in our day-to-day work at the agency, we’ve observed that the typical SaaS SEO strategy consists of two key parts:

• Optimizing core website pages: Optimizing the core pages of their marketing website (i.e. home, feature, solutions, pages) for high-intent, software category keywords (e.g. “accounting software”).
  
• Producing blog content: Creating and publishing some form of blog content on an ongoing basis, and often prioritizing keywords based on search volume rather than buying intent.

There may also be some link building or technical SEO tactics that happen. But these are really the two key parts to the strategy. 

Let’s take a closer look at each, and then below we’ll discuss the flaws of how this approach is typically executed in practice.

1. Optimize Home, Feature, and Solutions Pages for High-Intent Keywords

Most SEO agencies and SaaS businesses focus the majority of their SEO efforts on optimizing their core web pages — homepage, feature pages, and solutions pages — for a handful of target keywords. 

The standard process for this involves:

• Selecting primary target keywords for each page. These are generally the most obvious, high-value keywords that describe exactly what your product is (or what we call “software category keywords”) like “accounting software” or “enterprise CRM”. 

• Selecting supporting keywords for each page. These are generally pulled from a list of keywords that keyword research tools suggest including in your page in order to rank for the primary target keyword.

• Optimizing each page for their target keyword. Adding the target keyword or keywords into the title tag, page headings, and page subheadings throughout each page. And then using on-page SEO tools and sprinkling the supporting keywords throughout the body copy, or creating FAQs at the end of the page to include those keywords.

For feature pages, they’ll often optimize for software category keywords (e.g. lead generation software, social media management software, etc.). 

For solutions pages, they’ll often optimize for a particular industry or vertical they serve (e.g. marketing agency operations software, enterprise CRM software, etc.). 

Homepages will often be optimized for either a brand keyword, a software category keyword, or a mix of both (e.g. QuickBooks accounting software). 

This is the base-level strategy that B2B SaaS companies and SEO agencies implement. Once these pages are optimized, they build links to them in an effort to boost their rankings. But often they don’t end up ranking, for reasons we’ll explain below.

2. Create and Publish Some Form of SEO Blog Content

The second core part of the typical SaaS SEO strategy is to publish some regular cadence of blog content. And there are a few common ways that companies approach this:

• Outsource to freelance writers 
• Outsource to content agencies
• Using AI writing tools to create content at scale
• Hire an in-house writer or content marketer

We’ve written extensively about the pitfalls involved with each of these, which you can read about here and here. 

Outsourcing content is more common for SaaS startups, while larger and more established SaaS companies often opt to hire in-house. More recently, many companies have turned to AI writing tools to produce content faster and cheaper. But regardless of which option you choose,  we usually see one of the following two problems:

• The keyword strategy prioritizes traffic over conversion.  The predominant approach we see is what we call the “Top of the Funnel” volume-driven method:intentionally choose and prioritize keywords based on those that have the highest search volume, and write articles to rank for those keywords. These keywords are typically loosely related to the business’s target audience, but have no buying intent (and do not indicate people searching are looking to buy).
• The content lacks depth and differentiation. Whether it’s written by freelancers who don’t deeply understand your product, generated by AI tools, or produced by agencies doing surface-level research, the result is often the same. Most B2B SaaS content reads too generic with very little to no differentiation from the competitors. It might be factually accurate but it usually doesn’t offer unique insights, speak to specific pain points your product solves, and doesn’t give readers a compelling reason to choose you over competitors. We call content like this “Google Research Papers” because they resemble students writing a paper by Googling a topic and regurgitating what’s already been written without adding genuine expertise.

In our experience, neither of these methods are effective at generating trial or demo signups. 

To be fair, many agencies have improved their practices in recent years, and many B2B SaaS SEO agencies now talk about “high buying intent keywords” and “conversion-focused content.” But in our experience, even when the language has evolved, the execution often prioritizes traffic over conversions.

Let’s look at why.

3 Flaws with the Typical Approach to B2B SaaS SEO Strategy

Flaw #1: It’s Difficult to Rank Home, Feature, and Solutions Pages for High-Value Software Category Keywords

As we mentioned above, SEO agencies and SaaS companies tend to focus the majority of their SEO efforts into optimizing the core pages of their marketing website for high-intent, software category keywords.

But there are fundamental attributes of these pages that make it difficult for them to rank for highly competitive, purchase-intent software keywords.

Namely:

• Core website pages have limited space to include relevant SEO keywords. It often takes including 50+ supporting keywords (worked in naturally — not “stuffed” in) to rank for a given target keyword. And typical home, feature, and solutions pages don’t offer enough space in the headings and body copy to naturally include this volume of keywords.

• Core website pages are first and foremost meant to explain your features and solutions (not meet the search intent of specific keywords). The purpose of feature and solutions pages are to explain your features and solutions! There’s only so much you can modify them to address search intent. And yet, satisfying search intent is the key ranking factor used by Google and other search engine algorithms. Therefore, these pages have difficulty competing with other page types, such as dedicated landing pages or in-depth blog posts, which can leverage longer form content to deeply address topics and better satisfy search intent.

• Core website pages do not typically mention competitors, but ranking for software category keywords often requires including lists of software options. The intent of people searching for SaaS category keywords is often to see lists of SaaS solutions. And most SaaS businesses aren’t going to include lists of their competitors on their core website pages (that would make no sense!). So their pages aren’t going to outrank the SaaS review sites and list-style blog posts (often from direct competitors) that better meet search intent.

This is why, despite their efforts, many companies never see their core website pages rank for their intended keywords. 

Note: We’ve talked to (or are actively working with) multiple SaaS companies who have had such bad experiences working with SEO agencies that they’ve concluded they simply “can’t rank” for their top keywords. They’ve concluded that “Google just won’t rank us” on the first page. This is obviously not true and a shame.

By all means, companies should be strategic about optimizing these marketing site pages. But they should be aware that, as we’ve explained, they can be difficult to rank. And if these are the pages you put the majority of your SEO efforts into, you’re unlikely to see great results from SEO.

In addition, as we’ll demonstrate next, you’ll leave a ton of high-value keyword opportunities on the table — even if you get those pages ranking for their intended target keywords.

Flaw #2: There Are Way More High-Intent Keyword Opportunities Than You Can Reasonably Rank for with Feature and Solutions Pages

How many feature and solutions pages does a B2B SaaS marketing site typically have? In our experience, with the exception of “all-in-one” platforms that offer extremely large feature sets, it’s less than ten. 

Of those, maybe 2–5 of them have enough relevant content to be morphable into something that could rank for a valuable, competitive target keyword (per the issues we discussed above).

So, at best, most SaaS websites can only rank for a handful of “Bottom of the Funnel” SaaS category keywords with their feature and solutions pages. And yet, as our work has shown, there are often dozens upon dozens of keywords with good conversion potential in your space! 

Many of our SaaS clients have 50+ keywords that indicate people searching are potential customers looking to buy. And if you only use your feature and solutions pages to target high-intent keywords, you’ll leave all of those remaining opportunities on the table.

This is where companies can leverage blog content to go after these additional high-intent opportunities (as we do at our agency), but most do not. 

Flaw #3: Blog Content Isn’t Used Strategically to Rank for Valuable Keywords and Drive SaaS Product Signups

As we discussed above, the predominant approach to SaaS blog content, whether produced by freelancers, agencies, AI tools, or in-house teams, tends to prioritize traffic over conversions. Companies choose keywords based on search volume rather than buying intent, and the content itself often lacks the depth and product expertise needed to actually convert readers.

As we’ve explained in our post on SEO content writing, ranking for keywords with blog content requires a much more strategic approach than simply “sprinkling” in keywords. So the “Sprinkle” method is wholly insufficient when it comes to ranking for keywords that have actual business value. 

The “Top of Funnel” (TOF) method — which is the predominant method used by agencies and companies that are genuinely trying to be strategic about content — can work great for driving organic traffic. But as we’ve argued in many articles such as those linked below, it often doesn’t end up producing many leads.

Companies and agencies using the TOF method don’t choose keywords based on searchers’ intent to buy. They choose keywords based on how much traffic a given search query can drive to their site. And as a result, the majority of traffic they receive isn’t from people who are in the market looking to buy the type of software they sell, and conversion rates from their content tend to be very low. We’ve had countless conversations with companies who say “We have all this blog traffic but it barely converts” — this is why. 

You might think, “Well, even if the conversion rates are lower, doesn’t the increased search traffic make up for that?” It’s a good question, but in our experience, the theory that TOF traffic eventually leads to conversions down the line (through email marketing, PPC remarketing ads, etc.) isn’t always true.

And this problem has gotten worse. With the rise of AI Overviews and zero-click searches, top of funnel informational content is increasingly being summarized directly in search results. The traffic that TOF content used to generate is shrinking, while bottom of the funnel, high-intent content remains largely unaffected because searchers with buying intent still need to click through and land on your website to sign up and use the service.

In fact, as we’ve explained and demonstrated in numerous articles and B2B SaaS case studies — such as our foundational article on SaaS content marketing, our article on Pain Point SEO, and our Geekbot case study — not only do BOF, high-intent keywords produce significantly higher conversion rates, they also tend to produce a higher volume of overall conversions. 

By choosing and prioritizing keywords based on purchase intent instead of search volume, companies can: 

• Strategically go after all of the remaining high-intent keyword opportunities that their core website pages don’t rank for.
• See significantly higher conversion rates and conversions from their blog content.
• Drive meaningful increases in trial, demo, and product signups as a result of their SEO efforts.
• Build an SEO strategy that’s more resilient to AI-driven changes in search.

In the next section, we’re going to walk through how you can execute this for your business and how we approach this at our agency.

Our 5-Step B2B SaaS SEO Strategy

We have written at length about every step of our SaaS SEO strategy. So here we’re going to list and describe each step in our process, and link out to the individual articles that dive deeper into each step.

At Grow & Convert, our B2B SaaS SEO strategy consists of the following:

• Step 1: Do keyword research to identify high-intent keywords.
• Step 2: Create a dedicated blog post for each keyword that deeply satisfies search intent.
• Step 3: Sell your product in each piece of content.
• Step 4: Fix and monitor for technical SEO errors.
• Step 5: External link building and citation outreach.

Let’s look at each.

Step 1: Do Keyword Research to Identify High-Intent Keywords

The most fundamental part of a SaaS SEO strategy is keyword selection. If you don’t pick the right keywords (ones that, if ranked for, will drive demos and trials), then nothing else in your SEO strategy matters:

• Your technical SEO doesn’t matter. (It doesn’t matter how well your site is optimized if it’s not ranking for keywords that bring in customers.)
• Your link building doesn’t matter (same reason).
• The number of blog articles you write doesn’t matter.

Thus, keyword selection is the most important thing to get right. 

We’ve written about how you can approach this step effectively in our article on SaaS content strategy where we . classify high buying-intent keywords into three categories. Any SaaS company can use this framework to identify the keywords most likely to drive conversions.

Software Category Keywords

These are keywords where someone is literally searching for your product or service, which means they’re in the market right now.

The obvious ones are easy to think of: “project management software,” “help desk software,” “CRM for small business.” But there are usually far more variations than you’d initially expect, and exploring all of them is where you find opportunities your competitors have missed.

• Use case variations: “[Use case] software,” “[Use case] tools,” “[Use case] apps”
• Industry variations: “[Industry] software,” “[Use case] software for [industry]”
• Business size variations: “[Use case] software for small business,” “enterprise [use case] tools”
• Integration variations: “[Use case] software for QuickBooks,” “[Use case] tools with Slack integration”
• Feature variations: “time clock app with GPS,” “[use case] software with [specific feature]”

The more use cases you have or verticals you serve, the more keyword opportunities exist in this category alone. A company with four use cases serving three verticals could have 12+ variations just from combining those dimensions.

Competitor Comparison Keywords

These keywords indicate someone is actively evaluating solutions, which means they’re in buying mode and close to making a decision.

• “[Competitor] alternatives”: Searchers who are either using a competitor and want to switch, or who are aware of that brand and exploring what else is out there.
• “[Brand] vs. [Competitor]”: Direct comparison searches where you can make your case head-to-head against a specific competitor.
• “[Competitor 1] vs. [Competitor 2]”: Even when your brand isn’t mentioned, you can create content comparing all three options and insert yourself into the conversation.

These keywords often have lower search volume but extremely high conversion rates because the searcher has unmistakable purchase intent.

Jobs-to-be-Done Keywords

These keywords describe problems your product solves, even if the searcher isn’t explicitly looking for software yet. The reason they still indicate buying intent is that the searcher needs a solution to a current problem, and your product is one of the best ways to solve it.

• “How to” keywords: “how to track employee time off,” “how to automate customer follow-ups,” “how to plan delivery routes”
• Template and checklist keywords: “[use case] template,” “free [use case] spreadsheet”
• Process keywords: “best way to manage multiple projects,” “ways to automate invoicing”

JTBD keywords are different from pure top of the funnel content because the searcher has a specific problem requiring a solution, not just idle curiosity about a topic. 

For example, “What is project management” has no buying intent because the searcher is just learning about a concept. But “how to manage a team inbox” suggests someone actively trying to solve a problem, and that person may be ready to buy software that solves it better than their current approach.

We don’t prioritize high-volume, top of the funnel keywords like “what is CRM,” “customer service tips,” or “project management best practices.” We also avoid keywords where the SERP indicates purely informational intent. If all the top results are Wikipedia, encyclopedias, and scholarly articles, the searcher isn’t looking to buy anything.

That said, these keywords aren’t useless. They can be valuable for building topical authority with search engines, increase overall traffic, and create internal linking opportunities to your core pages that target bottom of the funnel keywords. We just don’t recommend starting here because the conversion rates are so much lower, and in an environment where AI tools increasingly answer these informational queries directly, the traffic payoff is shrinking as well.

Once you’ve exhausted the high-intent opportunities, top of the funnel content makes more sense as a way to strengthen your overall SEO foundation.

Step 2: Create a Single, Dedicated Blog Post for Each Keyword That Deeply Satisfies Search Intent

As we mentioned earlier, ranking on the first page for a high-intent keyword requires a very strategic approach to content creation. You can’t just sprinkle in keywords and hope that your post will rank, especially for high-intent terms which are valuable and highly competitive. 

When it comes to Step 2 of creating your content, there are two key factors to be successful:

1. Create a dedicated page for each keyword.
2. Deeply match search intent with each piece of content.

Create a Dedicated Page for Each Keyword

One of our key learnings (and a differentiator of our agency’s strategy) is that the best way to get top positions for high-intent keywords is to create a dedicated page for each one — even when keywords are nearly identical and have similar meanings. 

As we discussed in our conversation with Bernard Huang of Clearscope, you only get one SEO title, one H1 heading, one meta description, etc. — and these are key ranking factors for getting top positions.

If you try to rank for multiple target keywords with one piece of content, it will often only end up ranking for one of them (or worse, you won’t match the intent of any individual keyword, and you won’t rank for any of them).

This is especially important for high buying intent keywords where competition is usually fierce. Your competitors are likely creating dedicated pages for these terms, and if you’re trying to cover multiple keywords with one piece of content, you’re putting yourself at a disadvantage from the start.

Deeply Satisfy Search Intent with Each Piece of Content

Satisfying search intent begins with analyzing the search engine results page (SERP) for your target keyword to understand a) which topics need to be covered in your article for it to rank and b) how you can differentiate or improve on existing results to get a top ranking position.

The problem is that most marketers stop at high-level intent categories like “commercial” or “informational,” and in our experience, that’s nowhere near enough. You need to understand the specific layers of intent for each keyword, which requires analyzing what’s already ranking and figuring out why Google chose those particular results.

We’ve documented the exact process we use when analyzing search engine rankings for target keywords in our post on SEO content writing. Before writing any piece of content, we spend time analyzing the SERP for the target keyword to understand what Google thinks searchers want. While the keyword research stage involves a quick SERP scan (a minute or two per keyword just to verify buying intent), the content creation stage requires a much deeper analysis. Here’s what that process looks like in practice.

1. Review the titles, page types, and sources of existing page one results

The titles and page types of currently ranking content reveal what format Google expects for your target keyword. You’re looking to understand whether the top results are mostly list posts (“10 Best…”), step-by-step guides, comparison articles, landing pages, or something else entirely.

For example, if you’re targeting “project management software for agencies” and the top results are all listicles comparing different tools, that tells you searchers want options to evaluate rather than a landing page pitching a single product. 

If you create a landing page when Google is ranking listicles, you’re unlikely to break onto page one because you’re not matching what searchers (and therefore Google) expect to see.

2. Identify the subtopics and sections covered in top-ranking articles

After you understand the format, click into the top 3-5 results and examine what topics they actually cover. What questions do they answer? What sections do they include? What information do they provide that seems essential to the topic? 

If every top result includes a section on pricing, that’s a strong signal that searchers expect pricing information and you should include it. If they all feature comparison tables, you probably need one to stay competitive.

This doesn’t mean you should copy your competitors’ structure exactly (in fact, doing so would make it hard to differentiate), but you do need to cover the topics that searchers expect. In our experience, missing a key subtopic that all the top results include can signal to Google that your content is incomplete, which makes it much harder to rank.

3. Look for gaps and opportunities to differentiate

While you need to cover the expected topics, you also need to give Google (and searchers) a reason to rank your content over what already exists. This is where you look for gaps in the current results. 

Are there questions that aren’t being answered thoroughly? Are the existing articles generic and surface-level, full of advice that could apply to any industry? Are they missing specific examples, real data, or expert insights that would make the content more useful?

The goal should be to create something that’s genuinely better and more useful than what currently ranks on page one. If you can’t articulate a clear reason why your piece would be more valuable than what’s already there, you probably need to rethink your approach before you start writing.

4. Analyze the sources that are ranking

Understanding who is currently ranking gives you a sense of how difficult it will be to compete for that keyword. If the top results are dominated by high-authority sites like G2, Capterra, and major industry publications, you’ll likely need to invest more heavily in content quality, promotion, and link building to have a shot at page one. If smaller blogs and direct competitors are ranking, the barrier to entry is lower.

You should also pay attention to whether any of your direct competitors are ranking for the keyword. If they are, study what they’re doing well and where they’re falling short so you can create something better. 

If none of your direct competitors are ranking, that might signal an opportunity where you can establish a presence in the SERP before they do.

This SERP analysis process is essential because when you nail search intent, two important things happen. First, readers spend more time on your post, click into different sections, and display on-page behavior signals that tell Google your piece is fulfilling their search intent, which leads to higher rankings over time. Second, the searcher feels like your brand actually understands their problem, which makes them significantly more likely to trust you, explore your product, and eventually convert.

The companies that skip this step and just start writing based on their assumptions about what the keyword means almost always underperform compared to those who take the time to understand what’s already working.

Step 3: Sell Your Product in Each Piece of Content

In search engine optimization and content marketing, there tends to be an aversion to selling products and services through blog content. Blogs are considered to be primarily for generating traffic and brand awareness, and most marketers think that you shouldn’t be too salesy.

But when you design your content strategy to go after high-intent keywords, where people are at the purchase stage of the buyer’s journey, a key part of meeting search intent is discussing your product! This is what people are literally searching for. They want to know about what your product does, how it solves their problems, and how it’s different from other products and services on the market.

Therefore, an additional key step to writing your content is that you need to discuss the details of your product features and differentiators. And this has implications on how your content is produced — the person writing the content needs to know these things. 

If you want to see actual ROI from your content marketing, you need to adopt the perspective that it’s okay to sell your product through your content, especially when you’re targeting bottom of the funnel keywords where selling is exactly what the searcher expects.

The key is that selling through content looks different than selling on a landing page. In content, you’re selling through demonstration and education. You’re showing how your product solves specific problems, walking through features in the context of real use cases, and explaining why your approach is different or better than alternatives. When done well, this doesn’t feel “salesy” at all because it’s genuinely useful information that the reader came looking for.

This is why we urge companies not to fully outsource their content to freelance writers or agencies, unless those freelance writers or agencies have a process for developing deep expertise in your product or service and its differentiators (most do not).

Think about what it takes to write a truly compelling piece of content that sells your product. The writer needs to understand the nuances of how your product is positioned in the market, why it’s better than competitors for certain use cases, and what specific features solve which customer pain points. A freelance writer does not know these things if they’ve never worked at your company, talked to your customers, or deeply used your product.

Some companies try to solve this by hiring writers with industry expertise, but that doesn’t fix the problem either. Outside experts may have general industry knowledge, but that doesn’t mean they think about the nuances of your space in the way you do. If you rely on their perspective, you’ll end up with a blog full of their ideas, not yours, and your company won’t have a distinctive voice or point of view.

At Grow & Convert, we solve this by interviewing the experts at our clients’ companies for each piece of content we create. This allows us to express the company’s expertise on each topic to create truly high-quality content. 

Before we write anything, we get on a call with someone at the client’s company who has deep knowledge of the topic (a founder, product manager, sales lead, or customer success manager depending on the subject matter) and we ask them detailed questions about the problem, how the product solves it, what makes their approach different, and what specific features or capabilities matter most.

This is in contrast to doing what we call “Google Research Papers” — learning about topics in Google and regurgitating what everyone else is saying (what many digital marketing agencies and freelancers do). 

With our interview-based approach, we’re not making things up or relying on surface-level research but capturing the actual expertise and perspective of people who know the product inside and out, and then expressing that in clear, well-structured content.

For example, in a piece targeting “help desk software for small business,” we wouldn’t just list generic features that all help desk software has. We’d explain what makes our client’s specific product better suited for small businesses, whether that’s pricing structure, ease of setup, specific integrations, or a particular approach to ticket management. This level of specificity is what converts readers, and it’s only possible when the person writing the content has access to real product expertise.

If you’re targeting high-intent keywords where people are actively looking for solutions, you need to actually present your product as a solution. Generic advice that avoids mentioning your product will not convert, no matter how well-written it is or how much traffic it gets.

To better understand how you can approach selling your product through your content, check out our post on SaaS content writing which walks through an example. 

Also, check out the SaaS content strategy post we shared above, which has links to a bunch of articles we’ve written for our clients. (We discuss our clients’ products in every article we produce.) 

Step 4: Fix and Monitor for Technical SEO Errors

Technical SEO — the process of resolving any technical website issues that might hurt your organic search performance — is a necessary part of SaaS SEO. 

However, while we occasionally run into larger site architecture issues with our SaaS clients, the need for ongoing technical SEO support is more common in eCommerce where sites can have hundreds of product pages that target tons of long-tail keywords (very specific product queries).

For SaaS companies with largely static marketing sites, technical SEO is less about ongoing optimization and more about getting the fundamentals right from the start, then monitoring to make sure nothing breaks. If you notice sudden drops in rankings (which can be monitored in tools like Ahrefs or Semrush, along with other SEO metrics), then it’s worth looking into whether technical SEO might be present. But otherwise, technical SEO for SaaS websites can usually be taken care of with a one-time SEO audit and occasional follow-up.

That said, there are several technical SEO fundamentals that we see SaaS companies get wrong, and these mistakes can significantly limit the ability to rank even if the content is excellent. 

Here are the key areas to get right: 

Host Your Blog on a Subfolder, Not a Subdomain

One of the most common technical SEO mistakes we see SaaS companies make is hosting their blog on a subdomain (blog.yourcompany.com) rather than a subfolder (yourcompany.com/blog). 

This matters because search engines treat subdomains as separate websites, which means the authority you build through your blog content doesn’t fully transfer to your main domain, and vice versa.

When your blog lives on a subfolder, every backlink you earn to a blog post strengthens the authority of your entire domain, including your homepage and product pages. When it’s on a subdomain, that link equity is siloed. 

We’ve seen companies make significant ranking improvements simply by migrating their blog from a subdomain to a subfolder (though the migration itself needs to be handled carefully with proper redirects to avoid losing existing rankings).

Set Up Proper Canonical Tags

Canonical tags tell search engines which version of a page is the “official” version when duplicate or very similar content exists across multiple URLs. This is important for SaaS sites because the same content can often be accessible through different URL variations (with or without trailing slashes, with different query parameters, through HTTP and HTTPS, etc.).

Without proper canonical tags, search engines might split the ranking signals between multiple versions of the same page, or worse, choose the wrong version to index. 

Most modern CMS platforms handle basic canonicalization automatically, but it’s worth auditing your site to make sure canonical tags are implemented correctly, especially if you have pagination, filtered views, or content that appears in multiple places on your site.

Submit and Maintain Your XML Sitemap

An XML sitemap is essentially a roadmap of your website that helps search engines discover and understand the structure of your content. For SaaS blogs, this means making sure your sitemap includes all your blog posts, is updated automatically when new content is published, and is submitted to Google Search Console.

While Google will eventually find most of your content through crawling, a properly configured sitemap helps new content get indexed faster and ensures that nothing important is missed. 

If you’re publishing content regularly, check periodically to confirm that your sitemap is updating correctly and that there are no errors showing in Google Search Console.

Check for JavaScript Rendering Issues

This is particularly important for SaaS companies because many SaaS marketing sites are built on custom platforms, React-based frameworks, or other JavaScript-heavy technologies that can cause rendering issues for search engines. If your content is loaded dynamically through JavaScript, Google may not be able to see or index it properly.

You can check for rendering issues by using Google Search Console’s URL Inspection tool, which shows you how Google sees your pages.

If the rendered HTML is missing content that you expect to be there, you have a rendering problem that needs to be fixed, either by implementing server-side rendering, using dynamic rendering for search engine bots, or restructuring how your content is loaded.

Configure Your Robots.txt Correctly

The robots.txt file tells search engines which pages or sections of your site they should and shouldn’t crawl. For most SaaS sites, the main concern is making sure you’re not accidentally blocking important pages from being crawled. 

We’ve seen cases where a robots.txt file left over from a staging environment was blocking the entire blog, or where overly aggressive rules were preventing search engines from accessing key content.

Review your robots.txt file to make sure it’s not blocking anything that should be indexed (your blog, landing pages, etc.), and that it is blocking things that shouldn’t be indexed (admin pages, internal search results, duplicate filtered views, etc.).

Ensure Your Site Loads Quickly

Slow-loading pages hurt both your search rankings and your conversion rates because users will leave before the page finishes loading. For SaaS sites, the biggest opportunities are usually unoptimized images, too many third-party scripts (analytics, chat widgets, marketing tools), and render-blocking JavaScript.

Use Google’s PageSpeed Insights tool to identify specific issues on your site and prioritize fixes based on impact. You don’t need a perfect score, but you should aim to pass Core Web Vitals thresholds and ensure your pages load quickly on mobile.

Implement Proper Internal Linking

Internal linking is one of the most overlooked aspects of technical SEO, but it’s also one of the easiest to fix. When you link from one page on your site to another, you’re passing authority and helping search engines understand the relationship between your content. 

For SaaS blogs, this means linking from newer blog posts to your most important pages (product pages, pillar content, high-converting articles) and making sure no valuable pages are orphaned without any internal links pointing to them.

As you build out your content library, develop a habit of going back to older posts and adding links to newer relevant content. This helps distribute authority throughout your site and can give newer posts a ranking boost.

For most SaaS companies, technical SEO is not something you need to obsess over or hire a dedicated specialist for. Get the fundamentals right, monitor for issues using Google Search Console and your SEO tools, and then focus the majority of your energy on creating great content and building links and citations which we’ll discuss next.

Step 5: Link Building

Link building — the process of generating backlinks to pages on your site — is helpful for supporting your website’s domain authority and keyword rankings. 

However, it’s key to understand that link building is a supporting element of a good SaaS SEO strategy. Sometimes agencies or companies think that link building is the thing that gets content ranking. But in our experience, it’s not. 

If you don’t get the key steps of creating your content right (i.e. creating dedicated pages for each keyword, and deeply matching search intent), no amount of outreach, link building, or internal links will get your content up to the first page. So, link building is something to do and pay attention to, but don’t expect it to be a magic bullet for your SEO campaign.

We’ve found that building links to individual articles can often give them a boost in rankings and help support content in getting up to the first page. Each month, we build links to different articles we’ve published as an ongoing effort.

There are several ways to build links, and the right approach depends on your resources and goals. Here are the primary methods we use and recommend for SaaS companies.

Guest Posting

Guest posting involves writing articles for other websites in your industry (or adjacent industries) that include links back to your content. This is one of the most reliable and scalable ways to build high-quality backlinks because you control the context in which your link appears and can ensure it points to the specific pages you want to rank.

To make your guest posting campaign effective, make sure that you are targeting sites that are relevant to your industry and have real audiences, not just sites that exist solely for link building purposes. Links from sites with genuine readerships carry more weight with search engines and can also drive referral traffic directly.

Digital PR and Media Mentions

As search is getting more competitive, you should also try to get your company, product, or expertise mentioned in news articles, industry publications, and other media outlets. This can include contributing expert quotes to journalists, publishing original research that gets picked up by other sites, or simply being newsworthy enough that publications want to write about you.

The advantage of PR-driven links is that they often come from high-authority domains like major publications and industry news sites, which can have a significant impact on your domain authority. The challenge is that PR is less predictable than guest posting, and you have less control over where links point.

Resource and Listicle Inclusion

Many high-ranking articles in your space are listicles or resource pages that mention multiple tools, products, or solutions. Getting your product included in these existing articles can be an effective way to build links and also drive referral traffic from readers who are actively evaluating options.

This approach involves identifying articles that rank for keywords relevant to your product (like “best project management software” or “top CRM tools”), then reaching out to the authors or site owners to request inclusion. 

The success rate depends heavily on the quality and relevance of your product, but when it works, you get a link from a page that’s already ranking and driving traffic. Having an affiliate marketing program significantly increases your success rate with this approach, since many of these listicle sites are monetized through affiliate commissions. If you can offer the site owner a way to earn revenue when their readers click through and convert, they have a much stronger incentive to include your product and keep the listing updated.

We prioritize link building based on which articles have already shown they can convert. When we run paid promotion to articles and see that certain pieces are generating conversions through ads, we prioritize those articles for link building because they’ve already demonstrated business value. If we can get them ranking organically for their target keywords, we’re confident they’ll continue to convert.

This approach ensures we’re not just building links to random articles, but rather investing our link building resources in content that we know will drive results once it ranks.

Citation Outreach for AI Visibility

Beyond traditional link building, there’s an additional tactic we offer clients who want to accelerate their AI visibility: citation outreach. This involves identifying which articles and sources are appearing most frequently in AI-generated answers for topics relevant to your product, then reaching out to those sources to get your product mentioned or included.

For example, if ChatGPT and Perplexity are consistently citing a particular “best project management software” article when answering product recommendation queries, getting your product added to that article (with accurate information about features and use cases) can directly improve your visibility in AI answers. 

This is essentially the same concept as getting included in listicles for SEO purposes, but with the added benefit of directly influencing AI-generated recommendations.

For most SaaS companies, we recommend treating GEO as an extension of your SEO strategy rather than a separate initiative. If you’re doing Pain Point SEO well, you’re already building the foundation for AI visibility. The additional tactics (citation outreach, content structure optimization) can amplify those results, but they’re not a replacement for ranking in traditional search.

To learn more about our approach to link building, check out our content distribution strategy article. 

Measuring Traffic, Keyword Rankings, and Conversions 

To measure B2B SaaS SEO performance, see what’s working and not working, and spot additional keyword opportunities, we track and report on a variety of metrics for our clients with the following tools:

• Conversions: We track and report on conversions using the Model Comparison Tool in Google Analytics. 
• Keyword Rankings: We use Ahrefs rank tracker to monitor rankings progress for each article’s target keyword. (You could also use Semrush, Google Search Console, etc.)
• Overall Pageviews and Organic Traffic: We set up traffic dashboards in Looker Studio (formerly Google Data Studio) that measure overall pageviews and organic traffic to our articles.

The most notable of these three KPIs is conversion tracking. Most SEO teams (in-house or agencies) don’t hold themselves accountable to leads generated from content. In fact, most don’t even report on this. But without conversion data, you are essentially conceding that your SEO strategy is traffic focused (because everyone tracks traffic). 

Check out our article on tracking conversions in Google Analytics 4 to learn more about how to measure conversions from SEO content. 

Want to Work with Us or Learn More About How We Approach Content Marketing?

• Our Agency: If you want to hire us to execute content marketing in this way, you can learn more about our service and pricing here.
• Join Our Team: If you’re a content marketer or writer and would love to do content marketing in this way, we’d love to have you apply to join our team. 
• Our Content Marketing Course: Individuals looking to learn our agency’s content strategy and become better marketers, consultants, or business owners can join our private course, taught via case studies, and presented in both written and video content formats. We include several details and examples not found on this blog. Our course is also built into a community, so people ask questions, start discussions, and share their work in the lesson pages themselves, and we, along with other members, give feedback. Learn more here or watch our video walkthrough here.

Wave Writer is our new AI writing tool, built to solve a fundamental problem with AI-generated marketing content. Unlike every other AI writing tool for marketers, Wave Writer ingests and understands your business, products, features, and value propositions before it writes anything.

Most AI writing tools let you upload past content, but only to learn your brand voice — your tone or style. But actually knowing your business, products, and target customers is very different from style. It’s transformative because the AI fills in the blanks and knows which arguments to make.

Style is easy — you can write something in the wrong tone and use ChatGPT to fix it. No big deal. But what separates good marketing copy from bad is what it says substantively. 

• What are the arguments? 
• What are you saying? 
• How are you positioning your products? 
• Which features are you choosing to emphasize? 
• What benefits are you pairing with them?

Most people complain AI writing lacks substance and spits out fluff. That’s because generic AI tools fill in the blanks using just their training data, resulting in generic copy that sounds exactly like what everyone else has already said.

Not Wave Writer. Wave actually knows your business. With that knowledge, it can: 

• Analyze the SERP for a keyword and suggest ideas that are meaningful and tailored to your business. 
• Take your outline and fill in the blanks with real knowledge of your arguments, positioning, and details.

Wave Writer is in beta, but we’re accepting a limited number of users. Here’s how it works — and what it can do.

Sources: Teaching Wave Writer Your Business

When you set up your Wave Writer account, the first step is to upload your sources. We recommend adding between 10 and 20 sources — things like blog posts, white papers, demo transcripts, your homepage, case studies — anything that clearly and accurately describes your product and services.

Wave Writer reads those sources and summarizes its understanding of your business in a document called your brand summary. 

You can then review that summary, verify its accuracy, and make tweaks or edits you see fit. This becomes Wave Writer’s understanding of your business.

If you add or edit a feature, or introduce a new customer segment or use case, just update the brand summary. It’s a living document that captures what your business does and how you talk about it.

Using your brand summary, Wave Writer can create a variety of marketing assets. Right now, we’re starting with three: super briefs, content drafts, and social posts.

Output 1: Super Briefs

In our survey of 50+ marketers about their AI writing habits, many told us they use AI just as much (or more) for research and outlining as they do for actual writing. 

So the first output we built into Wave Writer focuses on comprehensive analysis, ideation, and outlining for SEO-focused content. We’ve been using this internally, and it saves a ton of time. 

Here’s how it works: 

You enter an SEO keyword, and Wave Writer Googles it, reads the top 10 ranking pieces, and gives you a detailed analysis with ideas for angles, introduction options, an outline to get you started, and more.

It’s a lot more detailed and substantive than a typical “content brief,” which usually just covers basic formatting guidelines or H2s from SEO software. That’s why we’re calling it a “super brief.”

Here’s what a super brief includes:

• Keyword Analysis: Using our Pain Point SEO methodology, Wave Writer categorizes the keyword — whether it’s a category keyword (bottom-of-funnel), comparison/alternative keyword, jobs-to-be-done keyword, or top-of-funnel educational content. This guides how you should approach the content and whether to pitch your product.

• Search Intent: Identifies which ideal customer personas are searching this keyword and the pain points they want to solve.

• SERP Analysis: Reviews what’s currently ranking, uncovers patterns, and spots weaknesses in existing content you can exploit.

• How to Pitch Your Company: A detailed analysis of how to position your product or service for a particular keyword, including which features to emphasize or benefits to highlight.

• Introduction Options: Multiple blog intros in different styles that strategically position the piece, not just generic fluff intros.

• Detailed Outline: A full outline that reflects your business’s unique angle and expertise.

The key principle here is that Wave Writer can do all this because it knows your business. Without that understanding, it couldn’t suggest angles to pitch your product, write substantive introductions, or build a useful outline.

Here’s an example of a few sections from a super brief for Grow and Convert using the keyword “best content marketing agencies”:

Output 2: Content Drafts

We’ve also given Wave Writer the ability to produce full drafts from an outline. This is straightforward — you give Wave Writer an outline, and it turns it into a draft. But in our experience, the difference between using Wave Writer for this and using native LLMs like ChatGPT or other AI writing tools is transformative.

I actually wrote this blog post using Wave Writer’s content draft feature. You can see the entire post, along with all of my edits on what Wave wrote in this PDF. 

Here’s a specific example of what Wave Writer can do. For the super brief output section above, I only gave Wave Writer these instructions: “using the transcript, describe the key parts [of a super brief].” That’s it! It filled in all the details because it had read the transcript of my YouTube demo as a source.

Below is Wave Writer’s raw output for that section, before any edits from me:

[The super brief includes] keyword analysis using our Pain Point SEO methodology to categorize whether it’s a category keyword, comparison/alternative keyword, jobs-to-be-done keyword, or top-of-funnel. It analyzes search intent — which of your ideal customer personas are searching and what pain points they’re trying to solve. It does SERP analysis of what’s currently ranking, the patterns, and weaknesses you could exploit. Most importantly, it provides detailed analysis of exactly how you can pitch your company for that keyword — which features to emphasize, what benefits to highlight. It gives you multiple introduction options that position the piece strategically, not generic fluff. And it creates a detailed outline that incorporates your business’s unique angle.

How did it know all those details about what a super brief contains? Because I uploaded the transcript of my YouTube demo as a source.

In the YouTube demo, I outlined a hypothetical piece on eCommerce blogging strategy by asking Wave Writer to “explain the key parts of Pain Point SEO.” It nailed it because it had read our Pain Point SEO article in its sources. Wave Writer knew that Pain Point SEO prioritizes high buying-intent keywords over high-volume ones, focuses on three specific keyword categories, and a bunch of other details.

In our experience, this is nearly impossible with raw ChatGPT or other writing tools that fill in the blanks using their training data. That’s why everyone complains AI writes generic fluff — because most tools generate copy that’s just the average of what everyone else has already said on the topic.

But with Wave Writer, you get AI-assisted writing built on your brand’s arguments, ideas, products, features, and more. 

Output 3: Social Posts

Social posts are a key part of content promotion and amplification, but they can be tedious to write. So we built Wave Writer to help with that, too.

Using the same principle — if it knows your business, it can take rough ideas and produce copy aligned with how you’d actually write. Beats generic AI copy.

We built this to work in two ways: you can upload a piece of content and Wave Writer will create three LinkedIn-style posts (or Twitter threads); or you can give it an outline, and it’ll create social posts from that.

You can also upload examples of your existing social posts as style guides, so Wave Writer learns not just what to say (your business knowledge) but how you say it on social platforms.

Here’s an example of me uploading this entire post and Wave creating 3 LinkedIn style social posts from it: 

We’re Opening Wave Writer to Limited Beta Users

Wave Writer is now open for beta. If you publish content regularly and want AI assistance — or you’ve tried AI writing before and been frustrated with the quality — this is for you.

We’re offering a paid beta at $40/month. During the beta, we’ll walk you through setup: a demo, uploading your sources, creating your brand summary, and making sure everything’s configured correctly.

Ready to see it in action? Sign up for a free personalized demo with me. 

From several years of experience, as well as countless conversations with other businesses doing content marketing (both in-house and with agencies), we’ve developed a good sense of what businesses are looking for when they hire content marketing agencies, what they’re disappointed by in the ones that don’t work out, and what true growth looks like in a successful engagement. 

So, to help businesses choose the right content marketing agency, we’re going to share our most important learnings and the key factors that you should consider when evaluating different content marketing firms.

Then, we’ll share how we’ve addressed each of these factors at our agency. And lastly, since most companies like to evaluate multiple agencies, we’ll share the best content marketing agencies we’ve heard come up a lot over the years (including ours).

Below, we cover:

• 4 factors to consider when evaluating content marketing agencies
• Our agency’s process: How we’ve addressed each of these factors
• Best content marketing agencies to consider

Note: Many companies wonder if they should hire an in-house marketer instead of an agency. We discuss the pros and cons of both options in this post. 

If you’re interested in hiring our agency to do content marketing for your business, visit our work with us page.

If you’re interested in working for our agency as a content writer or strategist, check out our careers page (we’re hiring).

And if you’re interested in learning the strategy and processes we use to do content marketing, check out our course and community.

4 Factors to Consider When Evaluating Content Marketing Agencies

To begin, we’ll cover the 4 biggest factors you need to consider when evaluating agencies:

• Factor #1: What’s your content marketing goal?
  
  For example: website traffic growth, email newsletter growth, leads and sales — e.g., calls to discuss your service, trials/demos for SaaS companies, product purchases in eCommerce.
  
  And is the agency’s content strategy optimized to achieve that business goal?
  
  This is the #1 factor you need to be clear on. In our experience, most companies want leads and sales — i.e. real customers and measurable ROI! — while most content agencies are built to grow traffic and email marketing lists. This mismatch causes problems.
  

• Factor #2: Do they have a process for gaining product and domain expertise, and expressing that through content?

• Factor #3: Do they have processes to actively promote the content they produce?

• Factor #4: Do they have detailed case studies that demonstrate the effectiveness of their strategy?

Let’s look at each of these in more detail.

Factor #1: What’s Your Goal From Content (Traffic, Emails, or Leads and Purchases)? And Is Their Content Strategy Optimized to Achieve That Goal?

Companies have different mindsets regarding the goal they hope to achieve from content marketing. In our experience, most want leads or sales — whether that be eCommerce purchases, sales call signups, or trials and demos in SaaS — because they want measurable ROI out of all their marketing channels, including content. This makes sense.

But there are some, for example, later stage companies with existing large lead generation numbers, that may want to use content for traffic and email signup growth. Others just have a vague idea that they want to do inbound marketing, and may not even realize that this is a choice they can make (i.e. they assume content is solely for getting traffic and brand awareness).

The first thing to understand is that this is a choice. You can optimize content around metrics like website traffic and email signups (what most digital marketing agencies do), or you can optimize content for generating leads and sales (what our agency does).

If you just want website traffic to grow your online presence, it will be much easier to find an agency whose strategy aligns with your goal.

However, most businesses ultimately want to see ROI from content, which means seeing leads or purchases attributable to content and meaningful increases in revenue over time.

In our experience, this requires a very different content marketing strategy (like the one that we use and have explained at length in previous articles like this and this).

That’s why we think this is the first and most important consideration when evaluating content agencies: Know your goal and figure out if the agency’s strategy and process is built to satisfy it.

If your goal is customer acquisition, then ask the agencies you evaluate if that’s what their strategy is optimized for. Ask them to be very explicit about this:

• Is their process designed to produce content that gets leads and sales?
• How does it work to actually achieve that goal?
• Are they data-driven and can they prove that their process works?

If an agency is asked if their process produces leads and sales, they’re obviously going to say yes, so you have to be very specific in your questioning. Focus on the second and third questions above, see if they can explain exactly how their process generates service signups or product purchases (not email signups, those are very different). Use your gut instinct — if you can’t figure out how their process will get leads or sales to increase, it probably won’t.

The biggest complaint we hear from companies who’ve had bad experiences with agencies — and frankly, the biggest complaint we had in our past experiences working with agencies — comes down to misalignment between what the agency optimizes content for, and what the company actually wants. So don’t skip this factor.

Factor #2: Do They Have a Process for Expressing Product and Domain Expertise Through Content?

Second, regardless of what your content marketing goal is, it’s important for whoever is producing your content to be able to express domain expertise in a way that feels native to your brand.

This is especially true for B2B businesses whose target audiences are often advanced industry experts who need to be communicated with at an expert level. If you don’t speak to them at their level, you risk reputational damage and turning off potential customers.

However, expressing product and domain expertise is important in B2C, too. Particularly if you choose to optimize your strategy for leads and/or sales, the topics you’ll write on will be very product or service-centric. This means whoever is writing your content will need in-depth knowledge of your product or service, the nuanced pain points that they solve for customers, and the ways in which your product is differentiated from competitors.

Most outside agencies or freelance writers will not have this product and domain expertise, and therefore need to have a process for getting this information out of the minds of the experts at your company, and expressing it through your content.

With that said, what we’ve seen in the market is that many agencies and freelancers end up doing what we call “Google research papers.” Like a high school student doing a research paper, they Google around the topic they were given and regurgitate what everyone else is saying on a given topic.

Instead of producing engaging content, this is undifferentiated and generic. So, when evaluating agencies, make sure you ask them:

• What is their process for being able to write and convey your value props, benefits, messaging, and differentiators in a way that feels native to your brand?

• Do they even have one? And if so, how does it work?

Is it a one-off interview at the beginning of the engagement? Is it a few one hour calls? Do they regularly interview experts at your company on a piece-by-piece basis?

We have found the latter approach — doing interviews on a piece-by-piece basis — to be both extremely rare when working with outside agencies, yet the most effective approach for expressing product and domain expertise through content. This is the approach we take at our agency and what we think differentiates good and great content, which we’ll discuss more below.

Factor #3: Do They Actively Promote the Content They Produce?

Content writing is just one facet of the content marketing process. For content marketing to work, it’s also necessary to do content promotion. This is what drives actual traffic to your articles.

So, another key thing to understand is what the agency offers with regards to content promotion. Is it included in their service? Sold separately? And what exactly do they do?

For example, do they just share the content they write via your own brand’s social media marketing channels (tweet it out for you, share it on your LinkedIn page, etc.)? Because that’s something you could easily do yourself.

Or, if they rely strictly on search engine optimization (SEO), is there anything they do in the short term to help drive traffic to articles during the time it takes for them to rank?

This is a key issue to address because what an agency offers for promotion will determine how much you’ll need to do on your end to drive traffic to your articles.

Ensure They Don’t Use a “Keyword Sprinkling” Strategy and Call That SEO

We’ve spoken with several clients who’ve had bad past experiences with SEO agencies. And after digging into the content those agencies were producing, we’ve learned that they often use a “keyword sprinkling” strategy.

Essentially, they’ll create “SEO” articles by simply “sprinkling” a bunch of keywords throughout their articles. But as we’ve explained in our article on SEO content writing, ranking highly for valuable keywords takes a significantly more strategic approach than this. Specifically, for the most valuable and competitive keywords, you need to have one single article or landing page completely optimized for a single keyword.

If an agency says that they primarily rely on SEO to drive traffic, be sure to have them explain to you how they go about ranking content for specific keywords. Ask them:

• What’s your process for doing keyword research?

• How do you choose keywords to target?

• What’s your process for analyzing search engine results pages (SERPs)?

• How do you reflect those analyses in your writing to get articles to rank?

• Can you show us examples of articles you’ve written that are ranking highly in Google?

• Are you doing digital PR or building high-authority backlinks to the articles?

Content or SEO services worth hiring will be able to answer these questions in detail and show you results they’ve gotten for other clients.

Note: We’ve published a detailed article on our SEO writing process, which you can read here. We’ve also published a detailed case study on SEO rankings data from 20 active and former clients, which you can read here.

Factor #4: Do They Have Detailed Case Studies That Demonstrate the Effectiveness of Their Strategy?

It’s very common for content marketing companies to share a lot of theoretical advice and information, but show little to no data or case studies that back up what they say and prove that their strategies work. It’s also common for them to put up badges about having “award winning” digital marketing services, quotes from past clients, or random stats like “we grew X company’s organic traffic by 200%.”

These types of testimonials and unsupported claims are not reliable proof that an agency can do what they say. So, an essential thing to look for is whether or not an agency has published the results they’ve achieved for clients, and specifically explained the details behind how they achieved those results.

Otherwise, you just have to blindly trust their level of competency, which leads to very inconsistent experiences with agencies.

When reviewing agency case studies, look for details about the work behind the results. For example, if they’re claiming they increased traffic by some percentage for a past client, figure out:

• How many articles did it take?
• Did one article produce most of that or was it spread out?
• What keywords did they rank for?
• How and why did they choose those keywords?
• How long did it take to rank?
• What was the domain authority of that client at the start and end? Did they do link building?
• What didn’t work?

The more transparent agencies are with the results they’ve achieved and the ways in which they got those results, the more you can trust them to be able to replicate those types of results for your business.

Now, let’s walk through how our agency has addressed each of these factors, including the details of our content marketing strategy, our writing and promotion processes, and 6 long-form case studies we’ve published to demonstrate the effectiveness of our strategy.

1. Grow and Convert

#1. Our Content Strategy Is Optimized to Drive Leads and Sales

We’ve optimized our content marketing strategy to drive leads and sales (versus traffic and email signups) for two key reasons:

1. Most companies want to see ROI from content: Sooner or later, most brands that invest in a content agency want to see some form of measurable ROI. We learned early on that if we can show ROI to clients (in particular management and executive teams), the engagements last longer, allowing results to compound while making everyone happy.
   
   
2. There’s are people actively looking to buy the product or service you sell: For almost every business, outside of rare category-creating products, there is some significant volume of people who are actively looking to buy that type of product or service — or solve pain points that product or service solves. These people are Googling terms that indicate they are ready to buy. Our perspective is that it makes way more sense from a business standpoint that a content strategy goes after these ready-to-buy-now people first (where conversion rates are much higher), before trying to reach the people higher in the funnel.

We’ve written at length about how we drive leads and sales through content for different business types. Check out these articles for detailed walkthroughs on our philosophy and our process:

Our Philosophy on Content Marketing Strategy

• Pain-Point SEO: How to produce SEO content that drives conversions
• Mini-Volume Keywords: Why targeting small search volumes makes sense
• How to create a content marketing strategy: A 5-step guide

B2B Content Marketing Strategy

• A B2B content marketing strategy designed to generate leads & sales

SaaS Content Marketing Strategy

• How to create a SaaS content strategy that drives product signups

B2C Content Marketing Strategy

• B2C content marketing: A guide to drive sales with content

How We Hold Ourselves Accountable

For every one of our clients, we create an ROI graph like this one (a live graph from a B2B SaaS client we’ve been working with for over 2 years):

The horizontal lines represent the number of leads this client needs per month to break even on their monthly spend with us. Each month, we plot the number of leads from our articles on this graph. Then we report on our progress in relation to that break even number, so clients can see when they begin to have positive ROI.

We’ve written extensively about how we do this here and here, including more case studies and client data. Before we started our agency, this is the type of thing we were looking for but could never find. And we feel this is the number one differentiator of our agency.

#2. We Use an Interview-Based Writing Process to Express Product & Domain Expertise Through Content

We don’t produce articles in the “Google research paper” style we described above (self-researching a topic and writing what you find).

Instead, our writers start by interviewing people inside your organization who have the know-how and expertise to speak on that topic and convey how your product and your company has innovated or differentiated itself in the topic area of the article.

Thus, the writer is not asked to pretend to be an expert themselves. This is a massive shift from traditional content services and is essential to producing genuinely high-quality content.

We’re not talking about grabbing a few quotes from experts to throw into an article. We’re talking about hour-long recorded interviews where we shape an entire article around the viewpoint and knowledge of an expert inside your company, who can not only speak to the topic area but also tie-in your product.

This changes everything. It creates true thought leadership content, and adds genuine product expertise into our articles because we’re able to include copywriting on all the detail and nuance of how your product or service is differentiated, what it replaces, why features were designed in certain ways, and more that only experts inside your company would know.

#3. We Use a Two Pronged Content Promotion Process

We use a two pronged promotion strategy to drive both short- and long-term traffic to your articles as we wait for them to rank in Google. Specifically:

1. Paid ads / PPC marketing campaigns (short-term traffic): We use paid ads to promote content using two targeting methods: Cold audiences (using interest and demographic based targeting) and lookalike audiences (based on the client’s existing customer list or website visitors). We test paid channels such as Facebook, Twitter, Linkedin, and Google Ads — based on each client and where we’re most likely to reach their audience.
   
   
2. Manual link building (long-term traffic): When certain pieces start ranking for their keyword, we strategically deploy link building to boost them to page 1 — or the top of page 1 — in Google.

The combination of these two steps gives our pieces a short term boost in traffic followed by long term sustainable organic traffic that adds up from different articles and grows over time.

We do all of the above from our own budget, with no extra spend for our clients, making us a truly full-service agency. This is markedly different from other top content marketing agencies and something we’re very proud of offering our clients.

#4. We Publish Detailed Case Studies to Demonstrate & Prove the Effectiveness of Our Content Strategy

Here are 6 in-depth case studies we’ve written to demonstrate how we’ve executed our content strategy for real businesses:

1. B2C content marketing example: How we grew Cognitive FX to 70,000 pageviews in 14 months
   
   
2. Content marketing case study: How we scaled Leadfeeder’s signups to over 200/month
   
   
3. Scaling content: Expanding from bottom of funnel content to top of funnel (Geekbot case study)
   
   
4. Scaling SEO traffic from 920 to 14,577 sessions in 6 months (Circuit case study)
   
   
5. How to do B2B content marketing without domain expertise (Rainforest QA case study)
   
   
6. How to create a keyword strategy for a new, innovative product (Case Study of a video editing software client)

Finally, if you’re interested, you can learn more about our agency, pricing, and reach out about working with us here.

Client Reviews

While we believe in our services and often go above and beyond to get results for our clients, you don’t have to take our word for it. We have an average of 4.8 out of 5 stars on Clutch (a popular third-party review site). 

Here’s what a few of our customers have to say:

Next, we’re going to share 11 other content marketing agencies we’ve seen or heard come up over the years, so you can weigh other options.

Note: We haven’t worked with any of the following agencies directly, so we can’t independently vouch for the quality of their work. But that’s why we outlined the 4 key factors for evaluating a SaaS content marketing agency above, so you can evaluate them. If you want to reach out to these agencies, we recommend you ask them about each factor and evaluate for yourself if (and how) they have a process to address them.

2. Animalz

According to their website, Animalz provides content marketing services to enterprise companies, startups, and VC firms. They list having worked with companies such as Google, Amazon, Airtable, and others. And they provide a variety of services including SEO consulting, brand awareness, lead generation, product marketing, and promotion and distribution.

Animalz doesn’t have any reviews on Clutch at the time of writing. 

Visit their site for more information about their services, team, podcast, and more. 

3. Siege Media

Siege Media is an SEO-focused content marketing agency that offers SEO, content creation, graphic design, website design, and link building services to businesses. They list having worked with companies such as Zillow, Shutterfly, and Tripadvisor. And they say their marketing solutions have generated over $148,646,000 in yearly client traffic value. 

Siege Media currently has 4.9 out 5 stars on Clutch.

Visit their site for more information. 

4. Optimist

Optimist is an SEO-focused content marketing agency for startups and growth-stage businesses. They specialize in working with product-led companies, and list having worked with companies such as Contentstack, FairShake, and HelloSign. Their services are broken out into startup content marketing, SaaS content marketing, and B2B content marketing.

Optimist doesn’t have any reviews on Clutch at the time of writing. 

Visit their site for more information.

5. Codeless

Codeless is a content production company offering a variety of SEO, content, and PR services. They say they create a proven, customized workflow for every client, and list having worked with companies such as Monday, Zapier, ActiveCampaign, and others.

Codeless has 4.8 out of 5 stars on Clutch. 

Visit their site for more information. 

6. Omniscient

Omniscient Digital primarily serves fast growing B2B software companies. They claim to tailor their approach to your specific goals, but their main services include strategy consultations, content creation, optimization of existing content, link building, and technical SEO audits. 

Omniscient doesn’t have any reviews on Clutch at the time of writing. 

Visit their site for more information. 

7. Seer Interactive

Seer Interactive claims to be a full-service digital marketing agency with a wide variety of services including digital strategy, paid media, content creation (including white papers, infographics, blog posts, and video production), and more. They also offer a data analytics platform to help you identify and track business KPIs. 

Seer Interactive can be found on Clutch, however, they only have one review with a half star rating, so it’s unlikely that their Clutch profile is a complete representation of the company. 

Visit their site for more information. 

8. Graphite

Graphite uses AI to identify groups of keywords with similar intent and to guide the writing process. When it comes to writing, Graphite’s AI will produce an outline and a list of keywords to get your writers started. They also have a proprietary tool to help you with internal link building. 

GraphiteHQ doesn’t have any reviews on Clutch at the time of writing. 

Visit their site for more information. 

9. Intrepid Digital

Intrepid Digital gives you direct access to SEO marketing experts and data analytics. They also offer paid media, search engine marketing, content creation and strategy, conversion rate optimization that aligns with a great user experience, and more.

An overview of Intrepid Digital can be found on Clutch, however, there are no reviews currently.

Visit their site for more information. 

10. Power Digital

Power Digital is a robust digital agency whose services include web development, web design, influencer marketing, email marketing, and much more. They serve B2B, B2C, fashion, retail media, and private equity companies.

Power Digital has 4.8 out of 5 stars on Clutch.

Visit their site for more information.

11. Quoleady

Quoleady is a content marketing agency that helps SaaS brands show up at the top of Google and inside AI-generated answers. By combining SEO, LLM optimization, and strategic content creation, they make sure your brand stays visible in both search and AI discovery.

The team behind Quoleady has worked with 200+ SaaS companies, including well-known brands like PandaDoc, Expandi, Monday.com, and GetVoIP, helping them drive signups and organic growth through high-quality, data-backed content. Quoleady is also running LLMO for SaaS, the largest Reddit community dedicated to exploring how SaaS brands can appear in ChatGPT, Perplexity, and other AI search tools.

Quoleady has 4.9 out of 5 stars on Clutch.

Visit their site for more information.

12. Aimers

Aimers Agency is a performance-focused digital marketing agency specializing in paid acquisition for B2B SaaS and technology companies. Their services include paid search and social advertising, conversion rate optimization, landing page design, and in-depth analytics. What makes them stand out? They don’t just run campaigns — they act as an analytical powerhouse, continuously testing and optimizing to reduce your cost per lead while scaling volume. 

Visit their site for more information.

Want to Work with Us or Learn How to Implement Our Content Marketing Strategy?

• Our Content Marketing Agency: You can learn more about working with us here.

• Our Content Marketing Course: Individuals looking to learn how to grow their SaaS business with content can join our private course, taught via case studies, here. We include a lot of information and examples not found on this blog. Our course is also built into a community, so people ask questions, start discussions, and share their work in the lesson pages themselves, and we and other members give feedback. We also get on live Zoom calls about once a month and dissect members’ actual content strategies and brainstorm ideas on how we’d form content strategies for their businesses.

• Join Our Content Marketing Team: Alternatively, if this style of B2B content marketing appeals to you, consider joining our content marketing team as a writer or content strategist. We have awesome clients. We’re a remote company. We pay well. And you won’t have to stress about getting your own clients or spend a bunch of time doing outreach to get them.

We surveyed over 50 marketers, from freelance writers to C-suite executives, on how they’re using AI to produce marketing content today.

We received extremely detailed responses about the processes they’re using, the strengths and weaknesses of AI writing, the tools they rely on, and more.

Below is an analysis of those responses.

You can also download a spreadsheet of every single response by signing up for our newsletter. If you’re already subscribed, just check your email.

Survey demographics: Who we asked & selection bias

We sent this survey to our email list and shared it on social media. We estimate that it reached an audience of over 5,000 marketers. We received 53 responses.

That’s a roughly 1% response rate from “saw it” to “filled it in”.

Why does this matter? Because it’s extremely likely that the 1% who responded are more enthusiastic about AI than those that didn’t. This is known as survey selection bias.

As a result, our data likely over-represents marketers who like AI, and under-represents marketers who either haven’t tried it or maybe have tried it and didn’t like it.

Of the respondents, 84% identified as being in marketing roles.

The roles were fairly evenly distributed across freelance writers, employees, management, and executives.

A majority of the respondents were in the U.S. or Europe:

Most writers and marketers are using ChatGPT

We asked respondents about the AI tools they use in an open-ended question, allowing them to list multiple tools, list obscure AI tools, or self-built models.

We manually categorized each response into one of the tools below:

The results are overwhelmingly dominated by ChatGPT — 90% of the responses mentioned it. So the data below reflect marketers in various roles, mostly in the U.S. and Europe, primarily using ChatGPT, followed by the other two members of the current AI “big three,” Claude and Gemini.

83% of marketers have published AI-assisted content

The first and most fundamental part of this survey was to understand how much marketers are using AI assistance in writing.

We asked: Have you published AI-assisted content at all, ever?

Benji and I were shocked that this number was so high. We can’t say what number we expected, but it definitely wasn’t 83%.

This means that, in 2024, when large language models and AI tools are still in their early stages, the vast majority of marketers are already using them — not just for fun, but for actual published content.

This is significant. It means AI writing is happening. It’s here — whether we like it or not. And if it’s 83% today, what will it be next year or in 3 years?

But let’s be careful. This stat doesn’t mean a few things:

1. It doesn’t mean 83% of words in marketing copy are AI-generated. As we’ll discuss below, marketers are using AI in a variety of ways, from seeding ideas to solving tricky wording issues. Most are not just asking ChatGPT to write entire blog posts.

2. It doesn’t mean this writing is good. Below, we discuss how the biggest complaint — even of these 83% ‘yes’ respondents — is the hours of editing required to turn it into something publishable.

Most have published many AI-assisted pieces, not just one

We asked: How many pieces have you published that were assisted or written by AI?

This question aimed to verify whether we’re talking about marketers using AI assistance regularly or just dabbling in it once or twice.

Over half of the respondents had published more than 5 pieces with AI assistance.

This shows that marketers aren’t just dabbling; they’re consistently using AI assistance in their writing.

Those who aren’t using AI assistance cite poor writing quality

Next, we asked the 9 respondents who said they aren’t using AI: why not? The majority pointed to concerns about the quality of AI writing.

Here are some examples:

• “The writing style is that of an eager grad student. And oh so bland.”

• “AI produces content that sounds ok but lacks the depth needed to really address pain points and needs in an engaging way, so that you really feel heard and understood.”

• “Mostly, it’s pretty but meaningless marketing blah blah.”

• “Also, I find it unreliable. For instance, in one case the AI invented an interview partner for a customer case study who doesn’t exist, even though it was fed with the transcript of a real customer interview.”

These concerns get at the heart of the matter with AI writing:

1. It’s not great.
2. It can outright hallucinate (a well-documented issue).

Finally, one particularly notable response cited pride in their craft, which we resonate with. Using AI to help write feels like it defeats the whole joy of writing:

“I’ve been a professional writer for 16 years, so I have a process. I also enjoy the challenge of building a piece of content from scratch. Although I’m sure AI would make my process faster, where’s the fun in that?”

Regardless, this perspective only accounted for 17% of respondents. For the 83% who are publishing AI-assisted content, let’s see how they’re using it.

How marketers are using AI for writing: ideas, outlines & drafts

This is where we dive into the specifics of how marketers and writers are using AI assistants for content creation.

First, we asked: How exactly did you use AI to help write? What was your process like?

Many responses were incredibly detailed. One writer even shared a six-step process:

1. Interview with client — AI (otter) makes a transcript.

2. Claude fixes the transcript so it’s easier for me to read/scan.

3. I load my notes/strategy docs/instructions/tone of voice to a Claude project (or use one that’s preloaded)

4. I consider the angle I want, plan strategy and messaging, etc. Then I tell Claude to write me an outline based on those directions. I make edits.

5. I might also have Claude use the interview to answer a series of questions.

6. Depending on the project, I’ll have Claude write a first draft. I make edits.

We went through the responses manually and bucketed them into themes:

• Draft long-form content
• Outline/ideas/keywords
• Editing
• Writing headlines or meta info
• Summarizing text or interviews
• Writing social posts
• Marketing site copy
• Other business use cases

We then tallied how many of the nearly 50 responses addressed each theme.

Note that a single response often touches on multiple themes. For example, if someone says they use AI to outline and draft, that would add one count in both the “outline” and “draft” categories.

Drafting was expected to be popular

Drafting long-form content is exactly what we all expect to be the most common use case for generative AI writing assistance. Drafting a full blog post is time-consuming, as we know first-hand! If AI can speed that up, even a little, it’s worth it.

As it turns out, for these respondents, it’s worth it even if AI isn’t a great writer, even if it produces a lot of fluff, and even if you have to spend time editing (we’ll get into this later).

Which begs the question: If LLMs are useful to help write now, despite producing fluffy writing that needs heavy editing, how useful — and therefore ubiquitous — are they likely to be next year? Or in 3 years?

Plus — and we’re going to make a bit of a judgement here — most companies produce mediocre to bad long-form content anyway…with humans. We’ve been writing about this problem for years, long before ChatGPT came out (e.g. Mirage Content, first published in 2017). So, if a writer or marketer’s clients or bosses are expecting “mid” content anyway, what’s the harm in using AI to help produce this?

Editing and outlining was a surprise

What we didn’t expect was how many marketers use AI to help them with outlining and editing. We assumed they were feeding outlines and arguments they created, then editing AI’s drafts.

We thought the process must be:

Because if a human is going to produce an article, they must know about the topic, right?

Turns out, no.

Based on these survey responses, the average use of AI in the writing process looks more like this:

Each step could involve humans, AI, or a mix of both. Marketers are using AI in various ways at different stages of the process — some for research, others for outlining, summarizing human interviews, drafting, or editing a human’s draft.

Here’s a symbolic example of how extensively AI is used in the writing process:

“I use several AI tools to help generate ideas and outlines. I guide the tools to create something very close to what I am trying to convey. I use other AI tools to confirm and/or add more.”

We have to admit, this isn’t very “G&C”. We’re all about interviewing subject matter experts who know the topic better than your average reader, so this approach makes us uncomfortable.

In our view, if you’re asking ChatGPT to outline your arguments, where’s the originality in your article? The same goes for editing. How can the LLM edit without understanding the key arguments or your brand’s position on the topic? We haven’t seen any responses suggesting that folks are training custom GPTs on their brand material to write or edit. Most are using out-of-the-box ChatGPT.

But, as mentioned earlier, most clients and brands don’t prioritize originality.

If you’re producing top-of-funnel Google Research Papers anyway, ChatGPT can help with both the initial research (replacing your Google research step) and generating an outline, often in one go. It’s a very convenient process. We’ll demonstrate this with an example in the next section.

In fact, this response from a separate question of the survey perfectly summarizes the point:

But for the clients that were most demanding in terms of quality, I found this doesn’t work as well. My best writing comes from not using AI at all.

But most clients don’t want that high of quality. Most clients want something that is generic and familiar with a little extra on top. Most agency clients don’t know (or care that much) what kind of content actually produces results for their clients.

Overall, we found the detailed responses to this question to be a fascinating look into the workflows of different marketers using AI for content generation. Again, you can sign up for our newsletter here to get the full list of responses.

Why did marketers start using AI writing? Speed and research

To better understand respondents’ pain points, we asked why they started using AI in the first place.

Was it to solve a real problem, or just FOMO from the ChatGPT hype?

The following seven themes emerged from their responses:

• Speed/saving time
• Research
• Improving writing
• Ideation or outlining help
• Cost savings
• Staying cutting edge
• Overcoming writer’s block

It wasn’t surprising that speed and saving time were the main reasons people first tried writing with LLMs. Along with 14% citing cost savings, 68% of responses highlighted the obvious benefits of using generative AI for writing.

However, what we didn’t expect were:

• Using AI to improve writing
• Ideation and outlining
• Overcoming writer’s block

Using AI to improve your writing

We were surprised by how many people said they first started using AI to improve their writing — this was the second most common response. We’d assumed AI writing was seen as inferior to human writing, but using AI to improve writing? That’s a surprise.

To be fair, some referred to “editing” as small tweaks, like trimming sections or reworking sentences:

• “I needed help trimming some of my content so as not to be cut off in Google search results. I’ve also used it for research.”

• “…to help rewrite a sentence in an article…”

But others cited larger reasons, like this marketer struggling with product copy and using ChatGPT for ideas:

“I was writing about a product line from a company whose website was full of marketing guff; I had attempted to rewrite it from scratch several times, but it just wasn’t clicking so I finally plugged it into ChatGPT to see if it could give me a better angle.”

While we don’t know if ChatGPT’s output was useful or how much editing was required, the fact that a marketer turned to AI after several failed attempts to write what they were looking for shows how much marketers are already valuing LLMs for writing assistance — even if most aren’t using the copy verbatim.

Research, ideas, and overcoming writer’s block

The combination of AI being used for research (22%), ideation and outlining (22%), and overcoming writer’s block (8%) stood out as notable themes.

Remember, this question is about why they started using AI in the first place. Adding up those three percentages (though not entirely fair, as several mentioned multiple themes), more than half of marketers in this survey said their gateway to AI writing was getting help with the foundational legwork behind a piece.

This suggests that AI is helping produce the “Google Research Paper” we referenced earlier, but on steroids. Before LLMs, writers would use Google to research a topic, then build their arguments.

What’s compelling about using LLMs is that they assist with both research and outlining or writing — all within the same tool.

For example, say we are tasked with writing a piece on trimming trees. Sure, you can Google it and read a bunch of these articles:

You can also watch a bunch of videos like this:

But that takes time.

You have to consolidate the information yourself (take notes, organize bullet points, cite sources) and then start formulating a structure or outline for your article on tree trimming.

This is hard work, but it’s what writing is all about: organizing information, deciding what’s worth keeping, how it flows, and playing with the structure. Authors like John McPhee and William Zinser have written extensively on this.

The words are the end result, but it’s the arguments and their flow that matter most. And yes, that’s tough. It’s like solving a challenging puzzle — it taxes your brain. But that’s the point. It’s the mental equivalent of lifting weights. The whole point is that they’re heavy.

While this mental weightlifting is the hard-won reward of writing, it’s also the allure of shortcutting this process with LLMs. ChatGPT can handle much of this hard work on its own. It may not reach the level of a great writer, but the appeal of having a computer tackle these mentally taxing tasks is too strong for many — especially if your client or boss can’t tell the difference.

With AI, you provide a prompt, a topic, and other details, and it’s trained on data related to that topic (like tree trimming). It’s as if you’ve read 10,000 articles on tree trimming. It handles both the research and outlining in one go, freeing you from juggling all the ideas in your head.

Let’s continue with the tree trimming example in ChatGPT:

We asked it to draft the post itself, not just the outline, but you can see how using LLMs first for research, then for outlining or brainstorming ideas, can easily lead to eventually asking it to draft the post.

And off it went, drafting this article in just a few seconds:

Not to mention, it sold our fictitious tree trimming company so well:

We just weren’t aware we were offering a 10% discount.

The big editing question: How much (and what exactly) are marketers editing AI?

We asked about editing in two parts:

First, we asked how much editing they have to do.

60% of respondents say AI content requires more editing than human writing, with over 20% essentially rewriting it entirely.

But what’s more interesting are the details we got from our follow-up question:

Can you elaborate on what editing AI-written content was like for you? (What did you have to edit? What was it good or bad at? etc.) The more detail, the better.

You can download the raw responses if you wish to sift through them, but here are some highlights.

We created themes from these long-form responses, but most of the feedback was similar and can be summed up as simply “not great”.

Writers complained about:

• Bland, generic language that sounded robotic
• Lack of any personal anecdotes
• Gross inaccuracies
• Repetitive language
• Lack of “voice”

Here are some highlights:

• “Many sentences were just word salad. They gave no useful information or POV. Those were changed after conducting online research.”

• “It’s super repetitive so I often cut out unnecessary sentences. It also sometimes makes illogical connections between the beginning and end of a sentence. It’s usually good at finding a simple way to say things, although it still sounds pretty robotic, so I have to switch things up to sound more human.”

In fact, several respondents shared our own frustration from experimenting with AI writing: by the time you keep iterating on prompts to get it to improve, you might as well have written it yourself.

“A lot of generic content can be produced unless you get very good at writing queries. Writers need to be good at editing their own output so the bulk of the editing doesn’t fall on someone else. Sometimes it seemed best to draft the piece yourself.”

That said, few respondents reported minimal editing needs:

• “Minor tweaks here and there but definitely not bulk rewriting.”

• “As you well know, AI tends to be wordy and fluffy and corporate. But so is my human writer. I have told it not to use certain words (like ensure or essential). Now that my AI is somewhat trained, I mostly do tightening up.”

(Shoutout to the “human writer” that got dragged like that.)

“Mirage Writing”: The core AI editing problem

One response really captured the core issue with AI writing tools:

“Missed the main point(s) because it was relying on general information about companies or products like ours, without truly knowing our situation — even if I submitted that information as part of the prompt.”

To me, this highlights two fundamental issues with AI writing:

1. Style: Filler words and fluffy language. This feels like the easier problem to solve. Presumably, you can train these models on your style and voice, give it phrases to avoid, and over time it should cut the fluff enough to make the editing time worth it.

2. Substance: What the writing is actually saying. This, to us, is the bigger issue.

Let’s look at a slightly artificial but telling example. We asked ChatGPT to write 500 words on what differentiates Grow and Convert from other content marketing agencies:

Yes, our prompt is unrealistically short. But almost all of its arguments are from our website, so in effect our bare bones prompt is more like attaching an entire website of background info to the prompt.

While it got some basic facts right, and correctly noted our focus on bottom-of-funnel content, this writing has a classic AI problem: it sounds like it should make sense, but upon closer read, it doesn’t.

We call this Mirage Writing. (In a nod to our mirage content concept.)

For example, let’s analyze the header in the screenshot above: “Focus on High-Intent, Business-Focused Content”

Sounds fine, right? No, that’s the mirage! When you look closer, you realize something is off. Think about this phrase: “Business-Focused Content”. We’re a content marketing agency, so it’s all about content for businesses. We’d never specify that our content is business-focused — every content agency’s content is. Plus, “focused” is an odd choice. Our content is entirely for businesses, not just focused on them.

As another example, take this sentence:

“While they handle everything, they also ensure that the client’s voice and brand are at the forefront of all content produced.”

There’s a weird logical leap here. What does handling everything have to do with keeping the client’s voice at the forefront? How are those concepts related? They’re not. You could have an agency that only writes content, and that content keeps the client’s voice at the forefront.

Like a mirage, the closer you look, the more you realize what you want isn’t actually there.

We plan on writing another article on AI mirage writing. Yu can join our newsletter to get notified when it’s published.

What were their results?

After all of the discussion above on how they’re using AI assistance, we wanted to zoom out and ask these writers and marketers what end results AI-assisted writing gave them and their teams.

The question was:

What results did AI-assisted content get you? Did it produce more/better rankings, traffic, or conversions? How did it compare to human written content?

We bucketed the answers into these 5 themes:

Benefit 1: More content, faster

Unquestionably, AI is helping content writers produce more. If you recall the question about why they started using AI above, speed was the #1 reason. This question shows that generative AI is largely fulfilling that promise.

Here are some telling responses on this theme:

• “It’s just a lot faster for me to get my work done. I don’t have to outsource to another freelancer. I do about the same amount of editing. It costs me a lot less.”

• “More content because I got a jump start on the first draft.”

Benefit 2: Improving writing (surprising!)

The theme we were surprised by above came up again here in a big way: the second most common theme was AI helping writers and marketers produce better content.

As critics of AI writing quality, we were shocked, again, by this. Analysis of the actual responses on this theme was interesting.

First, there’s what seems to be “the small stuff”: writers saying it helps them with tricky copy situations. We get this — we’ve used AI when we’re out of ideas for a headline, title, or a tricky phase. Getting ideas that aren’t your own can be really helpful:

“It helps with coming up with better words for certain copy.”

But it’s not just spot help with one or two tricky phrases! Look at these responses suggesting AI is helping these folks in a real, substantive way with writing quality:

• “I feel like it addresses the customer’s needs better and leads us to write more sharply.”

• “Sometimes the AI generates content that I hadn’t thought of or which I didn’t realize was related to my primary topic.”

We loved this elaboration from one respondent of how they’re combining their own interviews with subject matter experts (SMEs) with ‘an AI critic’:

“The one skill we hold as humans is the ability to do interviews. We consistently interview our SMEs for our topics and for specific actionable insights. Human interviews combined with an AI critic is doing wonders for us.”

Finally, several respondents noted its utility in the early idea stage:

• “My main reason for using AI was to help me get a head start on topics I already wanted to write about or to confirm topic ideas as viable (by providing output that seemed to be more solid than I could have provided right off the bat). I found using the AI helpful to give me directions for my own research.”

• “In some cases it did help because it gave me ideas. Like FAQs.”

• “Better SEO starting points.”

These touch on the theme mentioned above about AI being like having a researcher who’s read the entire internet, combined with a (flawed or immature) writer. Even if the writing is generic and fluffy, the fact that it can summarize a ton of research you’d have to do on your own is a massive time saver.

This response encompasses that viewpoint well:

“I would say that the biggest impact wasn’t in the results but in the process. AI allowed us to cut down on the work other folks (who are the experts) had to do in order to get me up to speed to write. It’s less about what the content did and its quality and more about how it can function as a tool to get information, especially explanations in layman’s terms, quickly.”

Benefit 3: Better marketing results (also surprising!)

Even though we asked about rankings, traffic, and conversion results in this question, we were still surprised by how many responses said they actually got improved marketing results from AI-assisted writing.

For example:

“I’ve had AI assisted writing produce conversions and have great rankings.”

This result suggests a discerning approach to using AI assistance, rather than just copying and pasting what it produces:

“Yes, my content ranked on top SERPs. If you’d just copy the generic content, Google intelligent algorithms might flag it.”

This response, in particular, highlights a smart way of using AI to produce a high volume of content on a topic, which helped a key page (“pillar page”) rank higher:

“Built an entire topic cluster within a month for a pillar page which helped me to let it rank on page 1 for a very competitive keyword.”

Complaints on quality

Finally, several responses complained about or were lukewarm on the actual writing quality, such as “it was ok” and “articles were hit or miss”.

• “Articles were hit or miss but I do think this is a strategy that improves with volume.”

• “I didn’t find it to be particularly better than the stuff I wrote completely on my own.”

• “In some cases it did help because it gave me ideas. Like FAQs… and this helped with rankings. But it doesn’t perform better than human written content.”

AI writing is here, and if the quality issue is solved, it could become ubiquitous

This survey taught us a lot.

Mostly, it opened our eyes to how pervasive AI writing already is.

Remember, ChatGPT was released in November 2022, yet over 80% of writers are now saying they’re writing with AI assistance. The majority of those are finding it useful, despite its shortcomings.

It’s no secret that we’re a bit elitist about writing quality at Grow and Convert. We don’t shy away from that, and in many ways, we’re proud of it. As such, we’ve been public critics of AI writing.

In many ways, these results justify a lot of our criticism — many other marketers say AI writing is fluffy, jargony, and doesn’t say much. But what surprises us is how, despite these issues, it’s already helping so many marketers write more, faster, and better.

Even the marketers who acknowledge AI’s writing weaknesses are finding ways to get help from it.

This is what seems to be the biggest opportunity. As AI tools continue to develop at a ridiculously fast pace, someone is bound to create writing tools that produce non-fluffy content that requires less editing. Those will be the game-changers.

Coming soon: Our AI-writing tool that actually learns your business

So, we’ll close by saying that at Grow and Convert, we’re creating an AI writing tool that truly understands your business.

The AI writing tool we’re developing learns the substance of your brand, products, features, benefits, and differentiators by asking you to provide your existing content — such as your website, blog posts, webinars, sales call transcripts, whitepapers, and more. It then summarizes its understanding of all of this content for your confirmation and produces marketing content (LinkedIn posts, blog content, website content, etc.) based on its understanding of your business.

Sign up here to answer a few questions and join our early access list.

In this guide, we address that question using data from over 40 clients. 

First, it’s important to recognize that many factors affecting rankings aren’t easily quantifiable (e.g., writing style, topic coverage). Therefore, we start by examining easily measurable factors — such as time, number of published posts, and domain rating — to understand how they influence first-page rankings.  

Next, we explore various other, less quantifiable factors and explain our approach to handling them.

Table of Contents

• How does time affect the likelihood of ranking on the first-page of Google?
  
  
• Does domain authority matter?
  
  
• What are the key factors for high rankings and how can I achieve them quickly?
  
  
• What can I do to drive leads while I’m waiting for rankings to take hold?

How Time and Domain Rating Affect First-Page Rankings

(Note: The data presented here reflects results from our specific process. If you take a different SEO approach, your results may vary.)

To understand the impact of time and domain rating on achieving first-page rankings, we first analyzed the average number of first-page rankings our clients have achieved each month while working with us.

(Note: Many Google results now feature infinite scroll, meaning there isn’t a traditional “page one.” So, when we refer to page one, we simply mean the top 10 results.)

The graph above shows the average number of top 10 rankings our clients achieve over time. The x-axis represents the number of months we’ve published content for them, and each blue dot represents the average number of top 10 rankings our clients have achieved by that time. 

For example, tracking from month 10, you’ll see that our clients typically have about 20 first-page rankings. That indicates that, on average, after 20 months of regular publishing, clients rank on page one for over 50 keywords.

The key takeaway is a clear upward trend: The longer clients work with us, the more blog posts they have ranking on the first-page, with an average of over 100 first-page rankings after three years. 

While that’s great news, you can argue that the more content you’ve published, the more likelihood you have at first-page rankings. Naturally, a client with 50 pieces published will have more first-page rankings than one with only five. (For most clients, we publish 3 articles per month, each targeting a single SEO keyword. You can read more about our process here.)

From here, we wanted to isolate the effect of time on rankings by controlling for the number of pieces published. This led us to ask:

Does time alone affect rankings? And if so, how long does it take to rank on the first-page of Google?

To answer this, we used the same data from the graph above but adjusted it by dividing the number of first-page rankings by the number of pieces published for each client. 

In this new graph, a y-axis value of 1.00 indicates that the client has one first-page ranking for every unique blog post we published.  

By examining the overall shape of the data in this graph, we observe that around month 15, each post averages close to one first-page ranking. 

(Note: This value can exceed 1 because some posts rank for multiple target keywords.)

This analysis answers the question, “How long does it take to rank on Google’s first-page?” On average, it takes us a little over a year for each piece of published content to reach page one on Google. 

As expected, the number of first-page rankings increases as more content is published.

Domain Authority Does Help Pages Rank Faster

Website authority is a widely recognized SEO term that refers to the strength of your presence on Google’s search engine. Different SEO tools use various metrics to assess this authority. For example:

• Domain Rating (DR) by Ahrefs which evaluates backlinks and the strength of those backlinks to determine overall site authority.

• Domain Authority (DA) by Moz predicts how likely a website is to rank, although the specific factors considered aren’t readily available.

Both tools provide a score ranging from 0 to 100, with higher scores indicating greater authority. However, it’s important to note that each tool measures different metrics.

Since many marketers rely on these scores to gauge their content’s ranking potential, we analyzed our data to see if it supports this idea. And it does. 

This graph shows the number of first-page rankings per post over time for two groups: 

• Clients with a Domain Rating (DR) above 50
• Clients with a DR below 50

For clients with a higher DR, the data reveals that they achieve around one first-page ranking per post just over a year after we begin publishing content for them.

In contrast, clients with a lower DR see about 0.6 first-page rankings per post at the same point in time. It’s important to note that the trend for the <50 DR group is still on the rise and hasn’t yet leveled off. This suggests that websites with lower DR could potentially reach the same number of first-page rankings as those with higher DR, but it would take longer. However, we currently lack the data to confirm this hypothesis.

Main Takeaway: It Takes Just over a Year to Achieve One First-Page Ranking per Post on Average

The key insights from this data are: 

• Time is the most crucial factor in determining whether a post will rank on Google’s first-page.

• On average, it takes a little over a year to achieve one first-page ranking for every post you’ve published.

• Website authority does play a role, but it’s not as significant as time. 

It’s important to note that this analysis focuses solely on time and domain strength as ranking factors. But many other factors influence rankings. 

To maximize your ranking potential, regardless of your domain rating or how long you’ve been publishing, you need to get these other factors right as well. 

In the following sections, we’ll explore the most important factors for ranking high on Google, based on our experience of helping over 80 clients rank for high-value keywords since 2017.

Other Factors That Affect Rankings (and How to Rank Faster)

In this section, we delve into the most critical factors that influence search engine rankings — factors that we focus on extensively for each client’s articles. While these elements are challenging to quantify and don’t lend themselves easily to correlation analysis, we believe they are essential for achieving higher rankings.

We will also briefly discuss routine tasks that are necessary but don’t provide a competitive edge on their own because they are standard practices (e.g., on-page SEO, mobile friendliness).

The Three Most Important Factors for Ranking on the First-Page of Google

1. Choosing Keywords Where You Have Topical Relevance

Topical relevance means that Google’s algorithm prioritizes sites that are authoritative on a specific topic, not just those with the highest number of backlinks. Essentially, Google wants to rank sites that it deems most relevant and knowledgeable about a given subject.

This concept has been widely discussed in SEO, including a nice example in the Ahrefs blog where niche cast iron cookware sites outranked a site with far more backlinks.

In our experience, we frequently see our clients’ posts outranking competitors with higher DA. This reinforces the idea that our client results are more influenced by relevance and time rather than just domain authority.

For instance, take a look at our client Cognitive FX, detailed in this case study.

They’re an awesome, cutting edge concussion treatment center in Utah that heals people who have been suffering from concussion symptoms for decades. 

Despite their impressive work, their Ahrefs domain rating is only 51, which is relatively modest.

We rank #1 for a lot of concussion keywords for them, and for most of those keywords, we’re outranking many medical sites with higher DR.

For example, look at the first-page results for the keyword “memory loss after injury”:

Despite having the lowest domain rating among the top four search results, we’re ranking #1 — outpacing sites like Mayo Clinic, which has a domain rating of 92.

Even in terms of backlinks, our specific page isn’t leading. We have no backlinks to that page, while #2, #3, and #4 results have 137, 40, and 1,417 backlinks, respectively.

So how are we achieving the top spot? Topical relevance.

Disclaimer: Of course we don’t know this for a fact. No one knows the exact “why” behind the results of Google’s search algorithm, but we can make educated guesses and we strongly believe this is true for our client results based on everything you’re reading in this post.

Our hypothesis is that Google recognizes Cognitive FX’s domain as being solely focused on concussions, which likely contributes to its high ranking.

In contrast, at the time of writing:

• The second result, MSKTC, provides rehabilitation for spinal injuries and burns, not just concussion rehabilitation.
  
  
• The third result, Headway, offers emotional support resources for a variety of ailments.
  
  
• The fourth result, Mayo Clinic, is one of the largest medical centers in the country, covering a wide range of medical services from complex surgeries to routine check-ups.

Cognitive FX, on the other hand, is highly-specialized in concussion treatment. This specific focus gives them a significant edge in topical relevance for concussion-related keywords, a trend we’ve observed consistently not just with Cognitive FX but with many other clients as well.

To summarize, while domain authority does play a role, it’s not the only factor. Focusing on bottom of the funnel keywords — those closely related to your niche and products — can help you compete effectively against higher DA sites. 

Topical relevance can be a powerful advantage.

If you’d like to learn more about topical relevance, check out our interview with Bernard Huang, the founder of Clearscope.

2. Matching Search Intent

Google’s algorithm prioritizes web pages that best fulfill the user’s search intent. If you meet that intent more effectively than other results, you’ll have a strong chance of ranking highly. 

While this might seem straightforward — like providing a list of accounting software for the keyword ‘accounting software’ — it can often be more complex.

Take the keyword ‘data visualization tool,’ for example. At first glance, you might think users are looking for a list of tools. But if you examine the SERP, you’ll notice different types of results:

• The top result is a list of tools.
• The second result offers definitions and examples.
• The third result is a product page.

So, which type of content should you create? Is the primary search intent for a list, informational content, or details about specific solutions? 

Moreover, the search intent can vary depending on the user’s role and industry. For example: 

• A data analyst with advanced technical skills might be looking for ways to enhance job efficiency.
  
  
• A business professional with limited technical expertise might need to present ideas to a corporate audience.
  
  
• A marketer might be seeking tools to create detailed reports for clients. 

Determining which persona to target involves understanding these layers of intent. 

To effectively address search intent, you need to conduct a thorough SERP analysis, which you can learn about here: How to Do SERP Analysis: Going Beyond the Basics. 

Once you understand the intent, the next step is to create content that meets those needs, which brings us to our next point. 

3. Writing Unique, High Quality Content

As the header suggests, writing great content involves two key aspects: uniqueness and quality. Let’s break down each component:

Uniqueness can manifest in several ways:

• Sharing original data: Provide fresh insights or data that others haven’t covered. 
  
  
• Offering a different perspective: Approach the topic from a new angle while still fulfilling search intent. 
  
  
• Interviewing experts: Incorporate insights from subject matter experts to add depth and authority.
  
  
• Discussing your product/service: For bottom of the funnel (BOTF) keywords, highlight how your product or service addresses specific pain points. 

If you want to write something unique, you can’t have AI write the article for you. The way AI works is that it pulls from existing material and creates something similar (i.e., it’s the opposite of creating unique content). 

Likewise, we advise against handing freelancers a brief and having them do their own research to write the article. We call this a “Google research paper” because the writer reads through the top results of Google and produces something similar to what already exists — it’s essentially the human version of what AI does. 

Creating high-quality content means delivering valuable information that aligns with the needs of the search term you’re targeting.

For BOTF keywords, high-quality content should not only rank well but also convert. You have to understand your audience’s knowledge level and position your product as the solution to their specific problem.

Here are some articles to help you write great content:

• Customer-Content Fit: A framework for producing content that attracts customers 
  
  
• The detail principle for writing good blog posts
  
  
• How to write great blog introductions (and why most are bad) 
  
  
• The Specificity Strategy: How to turn generic posts into stand out content
  
  
• Why your content needs “Originality Nuggets” to be effective

The Bare Minimum Tasks Needed to Rank

Lastly, here are three essential tasks often discussed in SEO that we consider basic “tickets to entry” for your site or your pre-publication checklist. 

(Note: If you’ve already handled these, feel free to skip to the next section.)

On-Page SEO

On-page SEO involves several factors beyond just fulfilling search intent, including:

• Using the keyword in the title
  
  
• Adding a meta description
  
  
• Internal link building
  
  
• Following URL best practices, like using the keyword in the URL
  
  
• Incorporating relevant keywords throughout the content
  
  
• Using relevant headers
  
  
• Ensuring your website has a clear, logical, and crawlable structure

While these tasks are important, they’re relatively straightforward compared to deeply analyzing search intent, crafting content to convert, and some of the other strategies we discussed earlier. These on-page SEO elements should be “checked off” for everything you publish.

User Experience (UX)

Another basic SEO housekeeping item is ensuring a good user experience (UX) and decent page load speed. Once this is setup properly, you shouldn’t worry about it too much. 

You can check your site’s performance with Google Page Speed. A high (or “green”) score isn’t necessary for most sites to rank well, but if your score is very poor, consider making improvements. 

Just don’t obsess over page speed. While it’s important for extremely competitive keywords (e.g., “buy flowers online”), for most companies targeting a wide range of SEO keywords, factors like topical relevance, matching search intent, and quality content are far more crucial. Instead, focus on whether your content fulfills search intent and the number of links it has.

Finally, make sure your site is navigable, modern in appearance, and both desktop- and mobile-friendly. 

Two Popular Pieces of Advice That Have Little Effect on Rankings

Update Content Regularly

Many marketers will tell you to update your content on a regular schedule because Google rewards content updates. In our experience, you only need to update content if the intent behind the keyword changes (or if you have something like a new feature to talk about that’s relevant to the keyword). Updating content solely for the sake of updating doesn’t necessarily lead to better results and often isn’t worth the effort. 

Build Lots of Backlinks

While backlinks do help improve rankings, they aren’t always essential. We often wait several weeks after publishing a piece to see how it performs on its own. 

If it ranks well right away or is steadily moving up, we’ll often leave it alone and focus our attention on other posts. However, if we want a specific post to move up faster or it doesn’t seem to be gaining much traction on its own, we’ll start building one or two links per month until we get the rankings we want.

How to Get Leads While You’re Waiting for Rankings to Take Hold

Although time is an important factor for ranking as we covered above, there are a few things you can do to drive leads temporarily while you’re waiting for high rankings:

• Paid ads can be a great way to drive traffic to your articles while you’re waiting for them to rank organically. In this article, we talk about common mistakes we see many marketers make that cause them to waste ad spend on hollow traffic that never converts. We also talk about what we do differently to improve ROAS.
  
  
• Social media can be an effective lead generation channel for B2C businesses because these buyers typically make decisions based on personal preferences and immediate needs. However, in our opinion, social media is less effective for B2B lead generation (with the exception of disruption stories, which we’ll cover below). B2B buying decisions are typically driven by specific needs (e.g., outgrowing a CRM) and often require a significant process change (e.g., company-wide training on a new CRM).
  
  
• Disruption Stories focus on highlighting the core problem your business was created to solve. Unlike SEO content, which is designed to rank for a specific keyword, disruption stories don’t target a specific keyword. Instead, they’re designed to be highly shareable on social media and to catch the attention of potential buyers who aren’t actively searching for a solution like yours. 

How to Work with Us or Learn More

• Work with our agency: If you want to hire us to create and execute an SEO strategy by identifying your best keywords, creating content that is laser-focused on ranking and driving conversions, and link building to improve your ranking positions, you can learn more about working with us here.
  
  
• Join our team: If you’re a content marketer or writer who wants to do content marketing in this way, we’d love to have you apply to join our team.
  
  
• Learn our methods in our content marketing course: Individuals looking to learn our agency’s content strategy and become better marketers, consultants, or business owners can join our private course and community, taught via case studies, and presented in both written and video content formats. We include several details and examples not found on this blog. Our course is also built into a community, so people ask questions, start discussions, and share their work in the lesson pages themselves, and we, along with other members, give feedback. Learn more here.