VISIBLEwith Usama KhanSeason 1 · Episode 3

Positioningfor AI Search: Why broad targeting kills your visibility

Narrow positioning now decides whether LLMs recommend your brand in AI search. Kateryna Abrosymova on why vague targeting makes you invisible to ChatGPT.

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If you sell a project management tool, you have more than 300 competitors. Kateryna Abrosymova, who runs the B2B content agency Zmist & Copy, has a lead with exactly that problem. They want to win a category dominated by players with massive budgets and millions of brand mentions. And they sell into "project management," one of the broadest categories in software.

Her answer was blunt. You cannot win that fight broad. You win it narrow.

This is the part most teams get wrong, and AI search is making the cost of getting it wrong much higher.

Vague positioning is now a visibility problem, not just a messaging problem

Kateryna has spent years fixing companies whose marketing stopped working. The root cause almost always traces back to positioning. In her estimate, about 90% of the companies she sees have a vague sense of who they target. They say they help "a bunch of different companies" and can deliver value to all of them.

That might even be true. But you cannot win fast in marketing on a broad strategy without a lot of money to spend.

Here is what changed. When a buyer asks ChatGPT or Claude "what's the best project management tool for a 20-person remote engineering team," the model picks from hundreds of options. The brands that get named tend to be the ones with the clearest positioning around that exact use case. Broad positioning gives the model nothing specific to grab onto.

So the companies with vague targeting do not just blend in with buyers. They become invisible to the systems buyers now ask first.

How positioning clarity actually feeds the model

Positioning clarity is not one document. It is the same story repeated across every surface a model reads.

Kateryna's sequence is specific. You figure out what makes you different and who your exact ICP is. You document that on your homepage. You build your site structure from there. Then every article, every landing page, and every LinkedIn post tells the same story.

When that story is consistent everywhere, the model has a clear entity to recommend. When your homepage says one thing and your blog says another, you have given it noise.

"Cited" and "recommended" are two different wins

I draw a hard line between being cited and being recommended, and Kateryna treats them as separate goals too.

Cited means a model references your page as a source. Recommended means the model names your brand as the answer to a buyer's question. Both matter, and they compound over time. You want to be cited on awareness-stage research. You want to be recommended on consideration-stage queries like "what's the best company for X."

But recommendation depends on the positioning being nailed first. The homepage, the blog posts, the landing pages all have to say the same thing before a model will confidently put your name forward.

Citability comes from things only you can say

To get cited, you need something genuinely unique in your content. An anti-plagiarism check is not enough anymore. You need an actual original idea on the page.

Kateryna's two methods are concrete. The first is a research report, because gathering real data from real people is hard, and that difficulty is exactly what makes it unique. The second works without that investment. Write a normal post, but build in your own approach, your client stories, and your named frameworks.

That last point matters more than it sounds. Naming your framework gives a model something specific to cite. It can say "this company uses a method called X, and here is how it works." A generic explanation of the same process gives it nothing to attribute to you.

This is also why she starts every engagement with expert interviews, and why she pushes writers to ask for specific examples and specific stories. Those details are what make content citable. They are the part AI cannot manufacture.

If your category is crowded and your content sounds like everyone else's, the problem is rarely your writing. It is that you have not decided who you are narrow enough for a model to repeat it. What would your positioning look like if you picked one ICP and built everything around it?

Want to see how this applies to your category specifically? Book a strategy call to map where you can win in AI search.

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