We Tested 50 Brand Queries Across 5 AI Platforms: Here's What We Found

AI search is no longer an experiment. It is the default discovery layer for a growing share of purchase decisions, vendor evaluations, and brand comparisons. But here is the problem: nobody agrees on how it works.

Ask ChatGPT to recommend a CRM and you get one list. Ask Perplexity the same question and you get a different list. Ask Gemini and the overlap is slim. For brands trying to show up in these answers, the lack of transparency is a strategic crisis.

So we decided to test it ourselves. Over three weeks in February and March 2026, our team at CiteDelta ran 50 brand and category queries across five major AI platforms: ChatGPT, Perplexity, Gemini, Claude, and Microsoft Copilot. We logged every brand mention, every citation, every source link, and every pattern we could find.

The results confirmed some hypotheses, contradicted others, and revealed a landscape far more fragmented than most marketers realize.

Methodology

We selected 50 queries spanning 10 verticals: B2B SaaS, e-commerce, professional services, fintech, health and wellness, travel, education, legal, home services, and food and beverage. Queries were split evenly between two types:

• Category queries (25): "What is the best project management tool for small teams?" or "Which CRM should a startup use?"
• Brand-adjacent queries (25): "Is [Brand X] worth it?" or "How does [Brand A] compare to [Brand B]?"

Each query was run across all five platforms on the same day. We recorded:

1. Whether the platform mentioned specific brands
2. Whether it provided source citations (clickable links)
3. Which domains were cited
4. Whether community content (Reddit, Quora, forums) appeared as a source
5. The total number of brands surfaced per response

We ran each query three times on different days to account for response variability. All responses were logged in a structured database for analysis.

Important caveat: This is a directional study, not an academic paper. Fifty queries across five platforms gives us 750 data points, which is enough to identify patterns, but not enough to make universal claims. We share our findings alongside data from larger studies (Otterly.AI's 1M+ citation analysis, BrightEdge's tens of thousands of prompts, Superlines' 34,000+ response dataset) to validate and contextualize what we observed.

Finding 1: Citation Rates Vary Wildly Across Platforms

This was the single clearest takeaway. The five platforms do not behave like variations of the same system. They are fundamentally different products with different source preferences, different brand densities, and different citation behaviors.

Here is what we observed across our 50-query set:

The gap between the most citation-heavy platform (Perplexity) and the least (Claude) was enormous. Perplexity provided clickable source links in 94% of responses; Claude provided them in just 4%. This aligns with Superlines' larger dataset, which found that citation volumes can differ by a factor of 615x across platforms.

BrightEdge's research on ChatGPT versus Google AI confirms a similar fragmentation: 61.9% of queries receive different brand recommendations depending on which platform you ask. Only 17% of queries return the same brands across all platforms tested.

What this means: If your AI visibility strategy targets a single platform, you are likely invisible on the others. Otterly.AI's analysis of 6.8 million citations found "very little overlap in what each AI model cites." The platforms do not share a citation index. They are separate ecosystems.

Finding 2: Reddit Is the Hidden Kingmaker

We expected Reddit to matter. We did not expect it to matter this much.

Across our 50 queries, Reddit was the single most-cited domain on Perplexity (appearing in 41% of responses) and the third most-cited on Copilot. Even ChatGPT, which historically leans on Wikipedia, referenced Reddit threads in nearly one in five responses.

This pattern holds at scale. Otterly.AI's analysis of over one million citations found Reddit.com as the top-cited domain on both ChatGPT and Perplexity. Averi.AI's B2B SaaS benchmarks report that Reddit accounts for 46.7% of Perplexity's top citations, 21% of Google AI Overview sources, and 11.3% of ChatGPT references.

The mechanism is straightforward: AI platforms treat Reddit as a proxy for authentic user sentiment. When someone on Reddit writes "We switched from Tool A to Tool B and our conversion rate went up 30%," that carries a type of authority that a brand's own marketing page cannot replicate. OpenAI's training data hierarchy reportedly includes Reddit content with 3+ upvotes as a Tier 2 source, and Google has licensed Reddit's data API for use across its AI products.

Reddit's Evolving Role

The picture is not static, though. Between October 2025 and January 2026, Reddit's overall share of AI citations dropped by roughly 50%, while YouTube's share increased. But there is a critical nuance: when Reddit is cited, it increasingly commands full authority over the response. Reddit's share of responses where it is the sole cited source increased 31% in the same period.

In other words, Reddit's role shifted from "one of many sources" to "the definitive source when it appears." For brands, this is arguably more important. Being the brand recommended in a high-authority Reddit thread that becomes the sole citation for an AI answer is extraordinarily valuable.

What this means: Brands with zero Reddit presence are flying blind. Even a handful of authentic, well-upvoted threads discussing your product can shift your AI visibility meaningfully. This is a core part of what we do at CiteDelta through our Reddit Seeding service, and the data continues to validate the approach.

Finding 3: Authority Signals Are Not the Same as Google's

One of the most common assumptions we encounter is that "if we rank well on Google, we will show up in AI answers." Our data, and everyone else's, says otherwise.

BrightEdge found that the overlap between top Google results and brands cited by AI has dropped below 20%. In our own testing, we identified multiple cases where the #1 Google result for a query was completely absent from all five AI platforms' responses.

The authority signals each platform prioritizes are distinct:

A few patterns stood out in our testing:

ChatGPT operates on consensus. It recommends brands that appear frequently and positively across many sources. Yext's analysis of 6.8 million citations describes ChatGPT's model as trusting "what the internet agrees on." In practice, this means brand mentions have a stronger correlation with AI visibility than backlinks (r = 0.664, per Averi.AI).

Perplexity operates on recency and third-party validation. It favors recently updated content and community endorsement. Brands that update pages regularly are cited 30% more often on Perplexity. News and journalism content dominates its citation behavior; earned media placements in major publications carry structural advantages.

Gemini operates on owned content. Otterly.AI found that 52.15% of Gemini citations came from brand-owned websites. It trusts what your brand says, assuming the content is structured and factual.

What this means: Your Google ranking is not your AI ranking. These are different systems with different inputs. A brand that dominates Google page one but has no Reddit presence, no review platform profiles, and stale content may be invisible across three of the five major AI platforms.

Finding 4: Small Brands Can Compete (and Sometimes Win)

This was the most encouraging finding. In 14 of our 50 queries, a brand outside the top five by market share appeared in the majority of AI platform responses. In three cases, a smaller brand was recommended more frequently than the category leader.

How? The pattern was consistent: these smaller brands had built a "citation architecture" across multiple surfaces. They showed up in industry directories, review platforms, "best of" roundups, Reddit discussions, and comparison articles. Their total web footprint was wide, even if their domain authority was modest.

This aligns with broader research. B2B brands that have mapped their AI citation footprint consistently find they appear in fewer than 30% of relevant category queries, regardless of their conventional SEO rankings. But the inverse is also true: brands with lower domain authority but broader third-party presence often outperform their larger competitors in AI answers.

The Minimum Viable Citation Footprint

Based on our observations, here is what the smaller brands that showed up consistently had in common:

1. Active review platform profiles (G2, Capterra, Trustpilot, or industry-specific directories). Agencies with Clutch profiles, for example, were cited 3.2x more often than those without directory presence.
2. Reddit presence with authentic, upvoted discussions mentioning the brand by name.
3. At least 2 to 3 earned media placements in recognized publications (not press release wires, but actual editorial coverage).
4. Structured, up-to-date owned content with clear headings, comparison tables, and FAQ sections.
5. Consistent brand name usage across all platforms, making it easy for AI to connect mentions.

The brands that were invisible, despite strong Google rankings, shared a different pattern: they had their own website and nothing else. No community presence, no third-party validation, no distributed footprint.

What this means: The AI citation landscape is more democratic than Google ever was. You cannot buy your way to the top with backlinks. But you can earn your way there through genuine, distributed presence. This is precisely the kind of visibility strategy CiteDelta builds for clients, and the data validates that it levels the playing field.

Finding 5: Content Format Matters More Than Content Volume

Not all content performs equally in AI citations. Across our 50 queries, we tracked which source pages were actually cited and analyzed their format. The pattern was unmistakable: structured, scannable content with clear data points was cited at dramatically higher rates than long-form narrative content.

This is consistent with larger studies. Research from multiple sources converges on the same conclusion:

Pages with organized headings are 2.8x more likely to earn citations than unstructured pages. Content with comparison tables achieves 47% higher AI citation rates. Pages with comprehensive schema markup are 36% more likely to appear in AI-generated responses.

The reason is mechanical: AI systems need to extract specific, citable claims from your content. A well-structured FAQ page mirrors exactly how AI presents information, in question-and-answer format. When your content already exists in the structure AI wants to use, you have done half the work for the model.

Conversely, dense technical content without section breaks prevents AI from isolating any single citable claim. You may have the best analysis in your industry, but if it is buried in a 5,000-word wall of text with no headings, no tables, and no clear takeaways, AI cannot extract it.

The "First 30%" Rule

One data point from Averi.AI surprised us: 44.2% of LLM citations come from the first 30% of a page's text. AI systems appear to front-load their reading, giving disproportionate weight to content near the top of the page.

This has direct implications for how you structure any page you want cited. Your key claims, data points, and brand positioning should appear early, not buried below a lengthy introduction.

What this means: Reformatting existing content can be more impactful than creating new content. A well-structured comparison page with tables, clear headings, and schema markup will outperform ten blog posts written in narrative style.

The Bigger Picture: Platform Trust Models

Stepping back from individual findings, our research reinforced a framework that Yext's 6.8-million-citation analysis also identified. Each platform has a distinct trust philosophy:

• Gemini trusts what your brand says. It prioritizes structured, factual content from your own domain.
• ChatGPT trusts what the internet agrees on. It looks for consensus across many sources, favoring brands with broad, consistent mentions.
• Perplexity trusts experts and users. It leans on industry-specific authorities, community forums, and recent editorial coverage.
• Claude trusts caution. It recommends fewer brands overall and rarely provides source citations, preferring to describe categories rather than endorse specific products.
• Copilot trusts Microsoft's ecosystem. It pulls heavily from Bing's index, LinkedIn, and news sources.

The practical implication is uncomfortable but important: there is no single optimization strategy that works across all platforms. An AI visibility program must be multi-surface by design.

What We Got Wrong (and Honest Limitations)

Transparency matters, so here is what we underestimated or could not fully resolve:

Response variability is extreme. We ran each query three times, and responses were not stable. Superlines' data confirms this at scale: only 30% of brands remain visible in back-to-back AI responses for the same query. There is less than a 1-in-100 chance that ChatGPT will give you the same brand list in any two consecutive responses. Our three-run average smooths this somewhat, but a larger sample would yield more precise numbers.

Claude is hard to study. With a 4% citation rate and minimal brand mentions compared to competitors, Claude's behavior was the least transparent in our dataset. It tends to discuss categories and tradeoffs rather than recommend specific products, making it genuinely difficult to assess brand visibility.

Temporal effects matter. Some of our queries were run during periods when specific brands were in the news, which likely inflated their mention rates. Averi.AI notes that pages updated within 60 days are 1.9x more likely to appear in AI answers, so timing is a real variable.

We are practitioners, not neutral observers. CiteDelta is an AI visibility agency. We build these strategies for clients. We have tried to present the data honestly and reference external studies where possible, but readers should know our perspective.

Implications for Businesses

Based on our 50-query study and the larger research landscape, here is what we believe businesses should prioritize:

1. Audit Your Cross-Platform Visibility

Do not assume your Google ranking translates to AI visibility. Run your key category queries across ChatGPT, Perplexity, and Gemini. Log which brands appear, which sources are cited, and where you are absent. The gap between what you expect and what you find is usually significant.

2. Build a Distributed Citation Footprint

The brands that show up in AI answers are not the ones with the best websites. They are the ones with the widest presence across review platforms, community discussions, industry directories, and editorial coverage. Think of it as building a constellation of mentions, not a single bright star.

3. Invest in Reddit and Community Presence

Reddit remains the most-cited social domain across multiple AI platforms. Authentic community engagement, not spam or astroturfing, creates the kind of user-generated endorsement that AI systems weight heavily. This is not a one-time campaign; it is an ongoing practice.

4. Restructure Your Content for Extractability

Audit your top-performing pages. Do they have clear headings, comparison tables, FAQ sections, and schema markup? Can an AI system extract a specific, citable claim from the first 30% of the page? If not, restructuring may deliver more AI visibility than any new content you create.

5. Optimize for Multiple Trust Models

Gemini rewards owned content. ChatGPT rewards broad consensus. Perplexity rewards recency and third-party validation. A single-platform strategy leaves you exposed. Build content and presence that satisfies multiple trust models simultaneously.

6. Monitor and Adapt Continuously

AI citation patterns shift quickly. Reddit's citation share dropped 50% in three months. YouTube's share surged. Brand visibility declined 35.9% across platforms in just five weeks during early 2026. Static strategies will decay. Build monitoring into your workflow and adjust quarterly at minimum.

Key Takeaways

1. AI platforms are separate ecosystems, not variations of Google. Only 11% of domains are cited by both ChatGPT and Perplexity.
2. Reddit remains the most influential community source for AI citations, even as its overall share fluctuates. When it appears, it increasingly serves as the sole authority.
3. Google rankings do not predict AI visibility. The overlap between top Google results and AI-cited brands has fallen below 20%.
4. Small brands can win by building broad citation architectures across directories, reviews, community forums, and earned media.
5. Structured content gets cited 2.5x more than unstructured content. Tables, FAQs, and schema markup are not optional.
6. The first 30% of your page matters most. 44.2% of LLM citations pull from early-page content.
7. Response instability is the norm. Only 30% of brands stay visible across consecutive AI responses. Consistency requires ongoing effort.

What Comes Next

We plan to expand this research to 200 queries across 20 verticals later this year, with weekly monitoring to track how citation patterns evolve over time. If you want to see how your brand performs across AI platforms, or if you want to start building the kind of distributed visibility that gets you cited, reach out to our team at CiteDelta.

The AI search landscape is still forming. The brands that map it now, rather than waiting for it to stabilize, will have a structural advantage that compounds over time.

This research was conducted by the CiteDelta team in February and March 2026. For questions about methodology or to discuss findings, contact us at citedelta.com.

Sources and Further Reading

• Otterly.AI: The AI Citation Economy (2026), 1M+ citation analysis across ChatGPT, Perplexity, and Google AI Overviews
• BrightEdge: ChatGPT vs Google AI 62% Brand Recommendation Disagreement, tens of thousands of prompts analyzed
• Yext: AI Visibility in 2025, 6.8M citation analysis across platforms
• Averi.AI: B2B SaaS Citation Benchmarks Report (2026), 680M citations analyzed
• Superlines: AI Search Statistics (2026), 34,234 AI responses across 10 platforms
• Semrush: The Most-Cited Domains in AI, 3-month citation study