The internet talks about you. AI is listening.

What the citation studies actually found

Several vendors have counted which domains appear in AI answers. They agree on the broad picture, community and reference sites rank high, and disagree on the details, because each one measures something different.

Sources: Peec AI, Profound, Semrush, Ahrefs. All four are companies that sell AI visibility tools, and none of them is a census of what every user sees.

Why assistants like these sources

Part of it is access. Google gained access to Reddit’s Data API in February 2024, and OpenAI announced a similar partnership in May 2024. Google also changed its ranking in late 2023 to show more first-person perspectives, and Reddit’s Google visibility rose sharply afterwards, according to Sistrix.

Part of it is probably what the content looks like. Our assumption, consistent with the studies above but not proven by them: discussions contain real comparisons, complaints and edge cases, the things a buyer asks about and a product page avoids. Wikipedia offers neutral, well-linked summaries. Both look like independent evidence.

And the Ahrefs finding adds a twist. ChatGPT retrieved Reddit pages often but rarely cited them. In Ahrefs’ words, it uses Reddit “to understand topics, gauge consensus, and build context—but it almost never gives Reddit the credit.” So a thread can shape what an answer says about you even when it never appears as a source. Counting citations alone will miss that.

The shortcuts that can cost you

Some guides recommend warming up accounts and seeding your brand into dozens of threads. Please don’t. Beyond being risky, it targets the exact thing that makes these sources valuable: that they are not written by the seller.

• Reddit’s rules ask users to participate authentically, ban content manipulation, and prohibit misleading others or impersonating an entity deceptively.
• Wikipedia’s conflict-of-interest guideline strongly discourages editing articles about your own company, and paid editors must disclose who pays them under the Wikimedia Terms of Use.
• In the US, the FTC’s rule on fake reviews and testimonials has applied since October 2024 and covers fake reviews, undisclosed insider reviews and incentives that depend on a review expressing a particular sentiment.
• In the UK, the DMCC Act explicitly banned posting and commissioning fake reviews from April 2025. EU consumer law also prohibits fake reviews. Rules differ by country, so check with someone qualified before running any review programme.

What you can do, legitimately

• Find the threads that matter. Search Reddit and the review sites for your category’s buying questions, and read the ones cited in answers where competitors are recommended. Note what people praise and what they complain about.
• Answer openly. If a community allows it, reply as your company, say who you are, and actually help. A clear, useful answer from a disclosed employee is not spam.
• Fix the product before the thread. If the same complaint shows up in every discussion, the problem is not your Reddit presence.
• Correct Wikipedia the proper way. Disclose your connection on the article’s talk page and request a specific edit, backed by independent reliable sources. Then let editors decide.
• Ask real customers for reviews, without conditions. Make it easy, never pay for positive sentiment, and never write them yourself.
• Earn coverage you could not have written. Original data, a useful tool or an honest comparison gives journalists and community members something to link to.

This is slower than a seeding campaign. It also keeps working when the platforms change their rules, and Semrush’s data shows how quickly the source mix can move.

Check whether it is working

Track two things separately: which sources are cited in answers to your buying questions, and what the answers say about you. Because sources can shape an answer without being cited, read the descriptions, not just the citation list. Our guide to mentions, citations and recommendations explains the difference, and the brand description audit shows how to spot a wrong claim that keeps coming back.