This post was sponsored by FirstPromoter. The opinions expressed in this article are the sponsor’s own.
For years, software companies have published pages that rank the best tools in a category and place their own product at the top. The tactic was cheap and easy to scale, and for a long time it helped shape what buyers saw.
In AI search, comparison listicles backfire. Google’s AI Overview quotes the listicle as a source, then recommends a competitor from your own cited list.
Your content only gets the citation. Meanwhile, your competitor gets the recommendation and the click. Your competitor gets the sale.
What makes your cited content recommend competitors?
Lily Ray quantified how often a brand’s own listicle earns the citation but loses the recommendation to a competitor.
In research published in June 2026, she analyzed 100 B2B “best software” queries in Google’s AI Overviews and checked the same queries three times between April and June.
The Results
Across the 80 queries that produced an AI Overview, self-ranked listicles were cited 323 times. In 224 of those cases, Google named a brand’s own page, then recommended a rival ranked inside it.
In other words, when a brand’s own listicle was cited, that brand was left out of the recommendation 69% of the time.
What’s the Difference Between Being Cited & Being Recommended in AI Search?
AI search produces two separate outcomes, and only one of them drives sales.
A citation means the engine named a page as one of the sources behind its answer.
A recommendation means the answer told the reader which product to choose.
The recommendation is what buyers act on.
A citation is easy to mistake for progress, because the brand still appears on the screen.
What an engine cites depends on the content of the page. What it recommends depends on what the rest of the web says about a brand: how many independent sites mention it, link to it, and review it.
Your goal should be to increase recommendations.
Why Does Self-Promotional Content Backfire in AI Search?
Google now treats self-ranked pages differently in its AI answers, Ray found.
The brands that win recommendations are the established names the web already covers.
Recommended brands had far more referring domains, and far more mentions across AI Overviews and ChatGPT, than brands that were cited and passed over.
On-page changes can’t fix this. The gap isn’t on the page; the citation-recommendation gap lies within how often the rest of the web covers the brand.
How to Measure Whether AI Search Recommends Your Brand
You can run this check for any category without special tools. Because citations and recommendations carry different intent, the goal is to separate two figures that usually get combined:
- How often your brand is cited (informational intent).
- How often it is recommended (transactional intent).
Step 1: Build Your Query List
Start with the questions a buyer would type, such as “best project…
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