Do AI search engines like ChatGPT or Perplexity favor big-name brands over smaller ones when deciding what to cite?
How do citation rates vary across brands in different AI search engines?
This explores whether AI search engines like ChatGPT, Perplexity, Gemini and Google's AI Overviews cite some brands more than others, and whether the engines differ from each other in how they do it.
This explores how often AI search engines name or cite brands, and whether that rate changes from one engine to another. A gap up front: the corpus doesn't break citation rates down engine by engine. What it does show is that the biggest differences are between kinds of brand, not between engines. Ranqo looked at more than 100 brands across five AI engines and found a steep ladder. Global names were cited 73% of the time, mid-market brands 44%, and niche brands 11% Do AI search engines favor well-known brands over others?. The ladder held even when the query didn't name any brand. That suggests the engines mostly repeat whoever is already prominent, rather than finding the best fit for the question.
The ladder makes more sense once you look at where the engines get their sources. In the same research, 78% of citations pointed to corporate websites, and ranked "best-of" listicles made up 21% Where do AI search engines actually pull their citations from?. The specific recommendations changed from query to query, but that narrow pool of sources stayed the same. So when someone asks why engine A named a brand and engine B didn't, the answer may often be which listicle each one happened to pull. Big brands appear in more of those lists, so their lead builds on itself.
Why does it matter whether you get cited? Because being named turns out to change what people do. One clickstream study found that when an AI assistant recommended a brand to people who weren't already its customers, searches for that brand name rose 4.3 percentage points. Visits to the brand's site rose 2.4 points, and visits to retailers rose 1.0 point Do AI assistant brand mentions drive real user behavior?. The same paper has a warning for anyone measuring "AI visibility." If you lump all brand mentions together, the effect looks about twice as large as it really is, because existing customers and passing mentions inflate it Does pooling AI brand mentions mask the true recommendation effect?. Many brand-citation dashboards likely carry that inflation.
The result you might not have expected: citations persuade readers whether or not they're relevant. In 24,000 Search Arena comparisons, users preferred answers with more citations, and irrelevant citations raised preference almost as much as relevant ones Do users trust citations more when there are simply more of them?. Being cited also doesn't mean getting the traffic. A randomized field experiment found Google's AI Overviews cut clicks to outside sites by 39.8% Do AI Overviews actually reduce clicks to publisher sites?. Ahrefs found clickthrough on the top organic result was about 58% lower for keywords that show an AI Overview How much are AI Overviews actually reducing organic search clicks?. Put together, for most brands the value is in being named inside the answer, not in the click that follows. And the engines decide who gets named mostly by how well-known a brand already is.
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Ranqo's analysis of 100+ brands across five AI engines found citation rates split sharply by brand tier: 73% for global names, 44% for mid-market, 11% for niche brands. The pattern holds even for unbranded queries, suggesting AI engines reproduce existing prominence hierarchies.
Ranqo's analysis found 78% of AI search citations point to corporate websites, with ranked "best-of" listicles accounting for 21% of all citations. This narrow source pool remains stable even as specific recommendations shift between queries.
When conversational assistants named brands to non-engaged users, same-name searches rose 4.3pp, brand site visits 2.4pp, and retailer visits 1.0pp in a clickstream panel. The effect concentrated on acquisition-like reach—bringing new users into the funnel—not accelerating existing interest.
The paper shows that naive pooled estimates (+2.08/+2.37/+0.52 pp) roughly double the true acquisition effect (+4.3/+2.4/+1.0 pp) when controlling for existing customers and incidental mentions. The inflation comes from pre-existing trends and ordinary repeat-customer behavior.
Analysis of 24,000 Search Arena interactions shows irrelevant citations boost user preference (β=0.273) nearly as much as relevant citations (β=0.285), indicating citation count functions as a decoupled trust heuristic.
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A randomized field experiment with 1,000+ users found AI Overviews reduced organic clicks to third-party sites by 39.8% while providing no measurable improvement in click quality or user satisfaction.
Ahrefs' December 2025 study found position-one CTR dropped to 0.016 for AI Overview keywords versus 0.039 for non-AI keywords, suggesting AI Overviews capture roughly 58% of clicks that would otherwise reach organic results.
Papers this line draws on 8
The research behind the notes this line reads — ranked by how closely each paper relates.
- Generative Engine Optimization at Scale: Measuring Brand Visibility Across AI Search Engines
- The Impact of Google AI Overviews on Publisher Traffic and User Experience: Evidence from a Field Experiment
- Impact of AI Search Summaries on Website Traffic: Evidence from Google AI Overviews and Wikipedia
- From Prompt to Purchase: How AI Brand Recommendations Move Consumers on the Open Web
- Google users are less likely to click on links when an AI summary appears in the results
- How AI Is Changing Search Behaviors
- New Research: AIs are highly inconsistent when recommending brands or products
- From Product Search to Preference Articulation: The Economics of Agentic Commerce