This post is sponsored by FirstPromoter. The opinions expressed in this article are those of the sponsors.
For years, software companies have published pages that list the best tools in the category and put their own product at the top. The trick was cheap and easy to scale, and for a long time it helped shape what consumers saw.
In AI search, comparison listicles go backwards. Google’s AI Overview cites the listicle as a source, and then recommends a competitor to your index.
Your content only gets a quote. Meanwhile, your competitor is getting recommendations and clicks. The competitor gets a canvas.
What makes your featured content stand out from the competition?
Lily Ray measured how many times a brand’s listicle won a coupon but lost a recommendation to a competitor.
In a study published in June 2026, he analyzed 100 B2B “best Content Strategy software” in Google’s AI Overviews and tested the same questions three times between April and June.
Results
Of all the 80 questions that generated the AI Overview, self-rating lists were cited 323 times. In 224 of those cases, Google named the product page, then recommended a competitor placed within it.
In other words, when citing a product listicle, that brand was left out of the recommendation 69% of the time.
What’s the Difference Between Attribution and Recommending in Search AI?
AI search produces two different results, and only one drives sales.
A citation refers to the engine that named the page as one of the sources behind its response.
A recommendation is a response that tells the reader which product to choose.
A recommendation is what consumers do.
The quote is easy to mistake for progress, because the product is still appearing on the screen.
What the engine says depends on the content of the page. What it recommends depends on what the rest of the web is saying about the product: how many independent sites are talking about it, linking to it, and reviewing it.
Your goal should be to maximize recommendations.
Why Self-Promotional Content Backfires in Search AI?
Google now treats standalone pages differently in its AI responses, Ray found.
Brands that win endorsements are established names that the web already covers.
The recommended products had the most referral domains, and mentioned in all AI Overviews and ChatGPT, there are products that were referred and referred.
On-page changes cannot fix this. There is no gap in the page; the citation recommendation gap is within how often the entire web closes the product.
How to measure whether AI Search recommends your product
You can run this check at any stage without special tools. Because citations and recommendations have different purposes, the goal is to distinguish two figures that are often conflated:
- How often your product is cited (informational purpose).
- How often is it recommended (commercial purpose).
Step 1: Create Your Questionnaire
Start with questions the buyer will type, such as “best project management software,” “Unique idea options,” or “the best Content Strategy software.”
Step 2: Record Quotes and Recommendations Separately
Run each one on Google and record two things: the pages Google cites as sources, and the products it recommends in response.
Step 3: Repeat Each Question
Use each question more than once, as the AI answers change from session to session.
Step 4: Enter Your Voice Assignment
Then you score the percentage of winning recommendations, rather than the number of citations received.
Step 5: Extend Auditing Outside of Google
The pattern is documented in Google’s AI Overviews, so start there. Run similar queries with ChatGPT and Perplexity to map out where publishers are coming from those engines in your category.
Ray’s research shows what work produces. For “the best LMS for marketing courses,” Google cited Oasis LMS repeatedly, both in the body of the answer and in the sidebar. Oasis ranks first in that regard. Google recommended Kajabi, Thinkific, LearnWorlds, and Teachable instead, each of which was named within the Oasis episode.
Ray found the same classification in every category, from CRM to help desk to SEO software.
Finding 2: Do AI Recommendations Come From Unpublished Cover? Yes.
Ray’s data shows where AI recommendations come from. Google relies heavily on third-party sites and users, with Reddit, Forbes, and YouTube among the most cited domains. Content independent of the product is gaining recommendations: reviews, comparisons, and channels published by someone other than the seller.
How Do You Find Independent Brands That Win AI Recommendations?
You need to increase the number of web pages about your product on domains you do not control, such as:
- Updates.
- Comparisons.
- Walking.
Each of these must be published by third parties. Not one placement at a time, but as a continuous output.
How To Do This Fast?
Give creators a financial reason to publish. When the creator earns money each time his sale converts a customer, he continues to write reviews, review comparisons, and publish walkthroughs, without having to release each piece.
You can start with a few creators and a revenue sharing agreement. What you produce is covering. What it does not produce, in itself, is coherence.
How to Maintain a Consistent Flow of Content?
Start an always-on channel: a managed program. Paying creators part by part gets you reviews here and comparisons there. The reference speed is always low because every new URL requires a new access. Fixed output takes structure: hiring good colleagues, tracking what each person produces, rewarding hard workers, and paying them on time. A membership program is that structure.
Third party affiliates that receive a commission when a customer they refer makes a purchase. They include niche site owners, YouTube reviewers, newsletter writers, and media publishers. To achieve it, they write reviews, record walkthroughs, and publish side-by-side comparisons on their sites and channels. That content is what Google pulls from when answering “best Content Strategy software” question.
Proof of Concept: AI-Driven Products Answers Already Implement Programs at This Scale.
Start any “best Content Strategy software” question and similar words occur again. Behind them sit networks of third-party sites that review and compare those products, earning a commission from the customers they refer. Their referral site statistics keep rising because the program is constantly sponsoring new installations.
Programs designed to overcome planning issues; programs designed for transfer volume do not. A program aimed at raw referral volume often attracts coupon sites, which drive clicks but rarely publish editorial content. A program aimed at AI recommendations hires partners who write and review for a living, and favors partners who have a real audience over partners who only distribute discount codes.
Telling a strong partner of weakness takes judgment. Signs to check for are long-term organic search performance, speaking honestly on partner sites they don’t control, and having a presence in more than one location. Partners who rank well in AI Overviews tend to have that record.
“Partners are one of the biggest sources of AI citations at the moment, yet most brands don’t even think about it. Being cited in AI Overview today doesn’t mean much by itself, because we see sites produced with AI being cited for a few weeks and then disappear once Google finds them. So check the organic history behind it first, look at the content of our partners, just investigate the content of flutu. A YouTube channel or promoter can save answered by AI, and they need the same check ” – Tautvydas Vasiliauskas
The reference site gained this quarter does not continue to gain on its own. The products that carry AI recommendations are those whose third-party coverage continues to grow, and that output depends on partners staying active.
Our partners are always active if the program is run well. Each task involved is simple. They are done by hand, together they eat up the hours the program should have saved.
Time is not the only thing at stake. AI systems draw recommendations from a collection of domains that talk about a product. Low-quality affiliates and their own submissions pollute that pool, and when they do, the program citations earned stop counting in the brand’s favor.
Keeping the pool clean requires fraud detection, checking partners, and preventing referrals, on an ongoing basis, not as a one-time cleanup.
This is a service operated by FirstPromoter. It tracks each partner’s performance and correlates it with revenue, so you can see which partners are generating sales, and which AI Overviews cite cover. It keeps partners motivated with contests, performance categories that pay high commissions, placement fees and targeted bonuses. Payments run on a scale from do-it-yourself to fully managed, and setup requires little or no developer resources.
The software will not select partners or shortlist them; that judgment rests with you. It manages the operations, so the coverage continues to meet without having to work continuously.
Stop Creating Content That Benefits Your Competitors. Start Building Links That Strengthen Your Brand.
The independent listicle had a great run, and that run is coming to an end. In AI search, Google makes recommendations to brands that the wider web already trusts, and builds that trust with personalized content.
An affiliate program is one of the most direct ways to produce content that gets you product recommendations, and you get paid based on results rather than adding value. It’s worth considering whether you’re starting a program or already using it. FirstPromoter offers a free trial to test the method.
Photo Credits
Featured Image: Photo by FirstPromoter. Used with permission.
Images Within Posts: Images by FirstPromoter. Used with permission.
