We founded Grow & Convert almost 10 years ago because existing content marketing agencies weren’t delivering what businesses actually needed: leads and sales. Instead, they focused on vanity metrics like social shares and traffic volume that had little correlation with revenue. That problem has only gotten worse in the AI search era with a new set of AI-related vanity metrics clouding the real purpose of content marketing.
Below, we outline the three major gaps that most content agencies have and how we designed Grow and Convert to solve them.
Gap 1: Agencies Are Unwilling to Be Held Accountable to Leads Generated
The real purpose of content marketing isn’t about how much you produce. It’s not the number of articles you’ve published or backlinks you’ve built. Give any CMO one piece of content that consistently drives qualified leads, and they’ll take it over a hundred that don’t.
It’s also not about surface-level metrics that might suggest customers — things like traffic, impressions, or social shares. As we’ve shown many times, those metrics don’t reliably correlate with conversions.
The purpose of content is to generate qualified leads that convert to sales.
This accountability gap has gotten worse in the AI search era. A new wave of vanity metrics tied to GEO (generative engine optimization) further clouds what drives business results. These include visibility metrics like “share of voice” in AI tools, or activity metrics like how many Reddit posts a team replied to in a given week.
We’re not saying these metrics have zero value. Share of voice can matter if you measure it on topics that actually drive customers. But these metrics shouldn’t outweigh the ultimate measurement of marketing success: sales and sales-related outcomes like qualified leads, pipeline, or closed deals.
That’s what brands ultimately want from content marketing, whether through traditional or AI search.
Gap 2: Most Agencies Can’t Produce Advanced or Specialized Content
Many of our clients sell B2B software or services with contracts over $100,000. Their customers are experienced buyers (CTOs, heads of HR, VPs of marketing) with decades of expertise in their field. They often ask advanced questions and may have already tried alternative solutions. Many of our B2C clients also sell to customers with deep knowledge in their space, like those seeking specialized medical treatments.
These customers are not beginners. They’re not asking Google or ChatGPT about basic concepts. They’re not looking for “beginner guides.” They’ve spent years in the industry. They’re researching in-depth solutions and expect content that matches their expertise.
But most agencies handle content creation in two ways, both of which fail to convert advanced, knowledgeable buyers:
Failed Method #1: Outsourcing to Freelancers
Agencies give freelance writers a brief or topic summary and ask them to cover advanced subjects like “sales CRM apps.” The flaw is obvious: the freelancer usually knows less about the topic than the target customer, yet they’re expected to generate the arguments themselves. So what do they do? They Google (or ChatGPT) the topic, and regurgitate the top results into their writing.
We call this a “Google Research Paper” because it’s like a student writing a paper for school. The result is unoriginal, uninsightful, and indistinguishable from countless others. It doesn’t impress or convert your best customers.
Failed Method #2: Producing AI-Generated Content
The modern twist on the freelancer-produced Google Research Paper is pumping out AI-written articles. It’s the same process, only now AI does the Googling and summarizing instead of the freelancer. The result is the same unoriginal, undifferentiated content, just with more em dashes. That’s why everyone calls it “AI slop.”
Many brands have come to us after trying both methods. They’re tired of churning out content that requires hours of editing just to get it to a level they’re proud of.
Gap 3: Content Teams Don’t Have a Clear AI Search (GEO) Strategy
Content and SEO used to follow a clear playbook: pick keywords, produce content, rank on Google, get traffic, generate conversions (assuming your keywords had high buying intent).
But as ChatGPT adoption grows and Google’s AI Overviews take over SERPs, most brands’ top concern is how to show up in AI search.
Founders, CEOs, and CMOs know they want to “get on ChatGPT,” but that’s usually where their clarity ends. They’re frustrated by vague recommendations and want help distinguishing between effective tactics and hearsay.
Every week, new “AI search tactics” emerge: Focus on Reddit. Change your headings to questions. Add LLMs.txt files to your site.
But what actually works? What doesn’t? Should they keep producing SEO content or pivot entirely to something else for GEO? And what should that strategy look like?
Most struggle with the balance between traditional SEO and AI search optimization. Many wonder “Is SEO dead?” despite the fact that many brands, including our clients, are seeing record leads attributed to traditional SEO today.
Finally, tracking remains an issue. How do you measure success in AI search? What’s hype and what’s a solid long-term strategy?
Brands want clarity in their approach and real data to back up their decisions.
Our Solution: A Two-Pronged SEO + GEO Strategy with Content as the Foundation
Solution 1: We Hold Ourselves Accountable to Lead Growth
Leads and sales are what matter most in any marketing effort. Whether it’s SEO, GEO, ads, or any other channel, the ultimate goal is always acquiring customers. All other metrics are, at best, “leading indicators.” That’s why our strategy focuses on maximizing measurable leads and sales from content across both traditional SEO and AI search optimization.
We don’t have a bias in the SEO vs. GEO debate. We simply follow the data to maximize client lead generation. And what we’re seeing across clients is clear: traditional SEO still drives the majority of leads, but AI search leads are steadily growing.
To capture both channels, we use our Pain Point SEO framework for traditional search and what we call Pain Point GEO for AI search.
Both strategies share the same foundation: publishing high-quality, bottom-of-funnel content on the client’s site.
These are topics where the user shows high buying intent. For example, if you sell accounting software, you want to rank when someone Googles “best accounting software” and when they ask ChatGPT “what are the best accounting software solutions available today?”
This is very different from top-of-funnel content where there is no buying intent (like “how to read a cash flow statement”).
In today’s AI-search world, both Google and ChatGPT generate their own answers for those queries, and the sources they cite get little to no traffic. Google’s AI Overview (AIO) is a good example.
Not to mention, top-of-funnel topics like this rarely convert to leads anyway.
We’ve published data showing this long before ChatGPT and AIO were around:
So top-of-funnel content suffers from a double whammy: low traffic in today’s AI search world and low conversion rates.
That’s why our process focuses on identifying bottom-of-funnel topics with high buying intent and publishing content around them.
Over the years, we’ve learned that these bottom-of-funnel topics fall into 3 groups:
Category Keywords
Comparisons and Alternatives
Jobs-to-be-Done Keywords
This is explained in more detail in our Pain Point SEO piece:
Next we’ll discuss how this content gets our clients visibility and high-intent traffic from both traditional SEO and GEO.
Solution 2: We Have a Proven, Repeatable Two-Pronged SEO + AI Search Strategy
Brands want to show up in ChatGPT and other AI tools, but most marketing teams don’t have a clear SEO + GEO strategy. Instead, they keep producing business-as-usual SEO content while randomly testing GEO tactics, with a new one hyped online every week (“Change all your page titles to Q&A format”, “Add summary bullets to each article!” ).
While some testing is necessary given how new AI search is, the foundation of both our SEO and GEO strategies remains the same: detailed, product-centric content that positions clients as the solution when users search for products or services in their space.
How does this BOTF, SEO-focused content help with AI search visibility? Two ways.
#1. Ranking on Google Helps You Show Up in AI Search
Because LLMs search the web for current information when answering user questions, the most effective way to gain LLM visibility is by ranking on Google for that topic.
The two most common AI search tools — Google AIO and ChatGPT — both rely heavily on Google search results. Google AIO is built directly on them, but even ChatGPT, as widely known, searches the web for queries it can’t easily answer from its training data alone.
In fact, our own data shows a 60–80% correlation between ranking our clients on Page 1 of Google for a given bottom-of-funnel term and being mentioned by ChatGPT for that same term.
#2. Long-form content helps position your brand for LLMs
The second reason is more subtle and often overlooked by marketing teams, but it’s equally critical. Long-form, product-centric content teaches LLMs what your product does, who it helps, what pain points it solves, which features matter, and how it’s better or different than competitors.
Why does this matter?
Because in AI search, especially ChatGPT, customers have long, detailed conversations with the tool. That means it understands their pain points at a far deeper level than Google ever did.
As a result, ChatGPT recommends products based on much more specific criteria than Google.
In this way, AI search is fundamentally different from traditional Google search, where users type much shorter keywords. ChatGPT’s detailed knowledge of user pain points means it looks for extremely specific products and features that can solve them, then surfaces those products for its users.
For example, a user may search Google for “best accounting software,” and that’s all Google knows: they want a list. But in ChatGPT, a user might have a long conversion about their challenges before asking for accounting software. Or even without the conversation, ChatGPT may already know from prior chats that the user runs a small business, has only two employees, and isn’t tech savvy — so it recommends products based on those highly specific details.
That means the more you teach ChatGPT (and other LLMs) who your product helps and how, in as much detail as possible, the more likely it is to recommend your product. You can read more about this here.
This level of detail is hard to achieve with Reddit or Wikipedia mentions. Those channels can influence LLMs by showing up in web searches, but they usually give you only a line or short paragraph to describe your product. Don’t get us wrong: Reddit, Wikipedia and other digital PR tactics are still valuable for GEO, but we view them as “boosters” of LLM visibility, while your own content is the foundation. This is explained more in Pain Point GEO.
To track all of this AI search visibility, we built our own AI visibility tool: Traqer.ai.
We weren’t satisfied with existing tools on the market, which are expensive and often generate random prompts that real users never type. We also believe tracking visibility on a single-prompt basis is flawed, so Traqer is built to measure visibility at a topic level, which gives a more holistic view.
Unlike tools that track via LLM APIs (which don’t give the same answers as the web experience), Traqer monitors actual search outputs. Every client engagement includes Traqer setup and reporting.
Finally, a critical added benefit of foundational owned content is that it also drives traditional SEO traffic and conversions. Despite what online marketing chatter suggests, SEO is still delivering sizable traffic and conversions for our clients.
At the time of this writing, most of our clients are only getting about 3% of their traffic from AI tools compared to SEO. For many of our clients, SEO traffic continues to grow and conversions are still primarily driven by SEO.
In other words, owned, product-centric content gives you a two-for-one benefit of getting AI mentions while still bringing in traditional SEO traffic and conversions.
Solution 3: We Produce Advanced, Industry-Specific Content to Power Both Strategies
The foundation of our two-pronged search strategy is extremely detailed, high-quality, product-centric content. It must cover your product, features, benefits, pain points solved, and differentiators at the same level your sales team or CEO would.
This kind of content can’t be created with AI tools or by freelancers who don’t truly understand your business.
Here are a few recent examples of blog posts we’ve produced for clients:
A post on neuroplasticity treatment for concussions for a concussion treatment center
A post on S3 file gateways for a company managing cloud file access
A post on ad network intricacies for a header bidding solutions company
Producing content like this requires two things most agencies can’t deliver:
Knowledge of actual customer pain points: Do target customers care about neuroplasticity treatment, cloud file synchronization, or website monetization strategies? We discover this through extensive interviews with customer-facing employees — sales, support, and product teams.
Ability to answer advanced questions at an expert level: We conduct follow-up interviews with subject matter experts inside client companies. This lets us capture exact brand voice and nuanced arguments, rather than generic points researched through Google.
We’re not talking about collecting a few expert quotes for articles. We conduct hour-long recorded interviews with internal experts and shape entire articles around your company’s perspective and deep knowledge.
This process produces content with sales-call-level argumentation that sophisticated customers notice and appreciate. And as noted above, it also gives LLMs the detailed, differentiated information they need to recommend your brand in specific contexts instead of defaulting to bigger-name competitors.
The Results Speak for Themselves
This strategy has driven consistent lead growth for clients across industries. We track both traditional SEO performance and AI search mentions, holding ourselves accountable to the metrics that actually matter: qualified leads and sales growth.
Here are a few examples of traffic growth from our content (organic and AI search):
Here are some examples of directly attributable leads from visitors landing on our articles:
You can find detailed case studies including one for Smartlook, the bottom graph above, here.
And here are mentions in ChatGPT, Perplexity, Google AIO via Traqer.ai for two bottom-of-funnel topics (10 prompts total) for one of our clients:
If you’re interested in working with us on content marketing that drives measurable results from both traditional and AI search, you can learn more about our approach and reach out on our work with us page.
