The platforms that crawl your AI site the most cite you the most (except one)

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Keywords: citation rate, ChatGPT, Claude, Perplexity, Gemini, GEO, Genymotion

Document ID: https://rozz.site/insights/crawl-citation-correlation.html#split1

Entry #5 · Mar 3, 2026

We tested 24 queries across four AI platforms. ChatGPT cites Genymotion 83% of the time. Claude cites Genymotion 21% of the time. Perplexity cites Genymotion 17% of the time. Gemini cites Genymotion 4% of the time. The first three track almost perfectly with how much each platform crawls our AI site. Gemini is a different story entirely.

Fresh data from our citation tracking tests on March 2 is available. We ran 24 queries. We ran the same 24 queries on all four platforms. We measured how many times Genymotion were mentioned (“brand mentions”). We measured how many times the sources linked to their site (“citations”). We then compared the results to the traffic we measure on our crawler logs on the AI site (rozz.genymotion.com).

We’ve been calling this a “mirror site” in previous articles. We’re dropping that name. It is an AI site. It is built for a different audience. AI agents are the intended audience. The AI site is more accurately compared to a mobile site. The AI site uses the same content. The AI site uses a different audience. The AI site uses a different artefact. We are not optimizing for citations. We are optimizing for AI agents.

Key Findings

The correlation (and where it breaks)

Here’s what we measured on March 2. We measured against crawl data from the same period.

| Platform | Crawling the AI site? | Weekly crawl volume | Citation rate | Brand mentioned | | --- | --- | --- | --- | --- | | ChatGPT (GPT-5.2) | Heavy, sustained since January | 1,200+/week | 83% (20/24) | 96% (23/24) | | Claude | Just activated (Feb 28) | 505 this week, was 21 | 21% (5/24) | 33% (8/24) | | Perplexity (sonar-pro) | Light, growing | 42 this week, was 14 | 17% (4/24) | 25% (6/24) | | Gemini | Not crawling | 0 | 4% (1/24) | 38% (9/24) |

For ChatGPT, Claude, and Perplexity, a straight line can be drawn. More crawling equals more citations. The AI site is doing what it’s supposed to do for these three. Gemini is something else because it ignores the AI site entirely.

ChatGPT: 14% to 83%

Before we built the AI site, genymotion.com showed up in roughly 14% of relevant AI queries. Eight weeks later genymotion.com showed up in 83% of relevant AI queries. ChatGPT cites Genymotion in 20 of 24 use-case queries tested. Brand mentioned Genymotion in 23 of 24. Same product exists. Same company exists. Same market exists. Same website exists. The only thing that changed is we built an AI site with structured content for AI agents.

Here’s the recap: GPTBot ’s initial mass crawl happened first. The crawl was 547 requests on January 7. This event started the whole article series. After that, sustained ChatGPT-User traffic happened. The traffic was 1,200+ requests per week. This week ChatGPT made 1,228 requests. The requests mostly hit Q&A pages (714). The requests also hit the homepage (307). The requests also hit GEO content pages (150). The crawler activity moved from training to indexing to citing.

The pages getting cited are consistently on these major topics. The topics include pricing plans. Pricing plans were cited in 22 visits this week. The topics include macOS compatibility. macOS compatibility was cited in 13 visits this week. The topics include free version availability. Free version availability was cited in 13 visits this week. The topics include Google Play Store setup. Google Play Store setup was cited in 13 visits this week. These are purchase-decision questions. Genymotion is in that answer 83% of the time.

When ChatGPT recommends Genymotion, ChatGPT links directly to genymotion.com pages. In most queries, ChatGPT ranks Genymotion at position #1. There are commonly multiple citation links per response. This reinforces legitimacy. This makes the ChatGPT answer a warm referral.

The remaining work is expanding content coverage into use cases where we’re weaker. CI/CD and app performance monitoring both came in at 13% citation rate. App development and manual testing came in at 63% citation rate.

Claude: reading the map, not the pages

Two weeks ago in Entry #4 (llm-bot-multiplatform-expansion), we wrote that we were waiting for ClaudeBot to come back for three weeks. The ClaudeBot had not come back. ClaudeBot came back. ClaudeBot made 505 requests this week. The number is up from 21. The increase is 24x.

The interesting part is not the number. The interesting part is what ClaudeBot chose to read. GPTBot does mass crawls. The mass crawls involve hundreds of pages in a day. Content is crawled first. Structure is optional. ChatGPT-User hits individual Q&A and GEO pages during live conversations. 176 Q&A pages were hit during the last four days alone. Both systems treat the AI site as a pool of content to pull from.

ClaudeBot is doing something different. ClaudeBot is reading the site’s organizational structure.

The topic sweep

On March 2 between 10:34 and 10:39 AM, ClaudeBot crawled 13 topic pages in sequence. ClaudeBot crawled one topic page every 20–30 seconds. Nearly the full topic taxonomy was crawled. The topic taxonomy is: android-versions, hardware-architectures, virtualization-technologies, arm-platform-and-gpu, billing-and-subscriptions, licensing-and-eulas, macos-security-toolkit, documentation-and-support, ci-cd-tools, network-security-toolkit, system-image-and-bios, software-installation-and-trials, root-access-and-tools.

ClaudeBot did something similar on February 28. That session mixed topic pages with GEO content pages. Enterprise features were included. Cloud platforms were included. VirtualBox compatibility was included. Hyper-V troubleshooting was included. The session included a total of 8 content pages plus 1 topic page in two minutes.

ClaudeBot is the only bot that systematically crawls topic pages. In the same four-day window, ChatGPT-User hit two topic pages. Both topic pages were pulled into live conversations by user queries. GPTBot, ByteSpider, PerplexityBot, and Meta AI had zero topic page hits.

What does “reading the map” actually mean?

Topic pages are the only pages on the AI site with CollectionPage schema. Each topic page lists every content page and Q&A in that topic. Each topic page includes titles, descriptions, and links. The topic pages serve as the site’s table of contents. The topic pages are not answers to questions. The topic pages are a map of what the site knows and how it’s organized.

By crawling all 13 topic pages, ClaudeBot has a complete picture of the site’s knowledge structure. ClaudeBot knows which topics this domain covers. ClaudeBot knows how many pages address each topic. ClaudeBot knows which keywords appear for each topic. ClaudeBot knows how individual pages relate to each other.

What we can’t explain is why ClaudeBot read zero Q&A pages. During the same time, ChatGPT-User read 176 Q&A pages. The content that drives 75% of ChatGPT citations was skipped entirely by ClaudeBot.

Three possible explanations

1. ClaudeBot is evaluating before committing. The pattern includes constant monitoring. The monitoring includes robots.txt and sitemap checks every 2–3 hours. The pattern includes a content sample session on Feb 28 with 8 pages. The pattern includes a structural assessment on Mar 2 with a topic sweep. This looks like a staged decision pipeline. The staged pipeline understands the site’s scope and quality through its taxonomy. The staged pipeline then decides whether to invest deeper crawl budget on individual pages. If this is correct, a bulk content crawl should follow. 2. Anthropic is building a different kind of index. A question exists about how Claude’s retrieval works. The question compares Claude’s retrieval to ChatGPT’s model. ChatGPT follows a “find page, index page, serve page” model. Anthropic could be building something more like a knowledge graph. The unit of understanding in a knowledge graph would be “what does this domain know about” instead of “what does this page say”. In that case, topic pages are exactly what you’d want to read first. Domain expertise would be built. A domain expertise profile would be built. A page-level retrieval index would not be built. 3. The Q&A gap explains the citation gap. Claude’s citation rate is 21%. ChatGPT’s citation rate is 83%. ChatGPT-User reads Q&A pages constantly. ClaudeBot hasn’t touched one in the last four days. Q&A pages are phrased as questions. Q&A pages match how users query AI. If ClaudeBot hasn’t indexed them, ClaudeBot misses the content format that matches how people ask questions. If ClaudeBot comes back for a Q&A crawl and Claude’s citation rate jumps, the jump would confirm this.

The crawl itself

Outside those content sessions, ClaudeBot runs a monitoring loop. The monitoring loop includes robots.txt plus sitemap.xml every 2–3 hours. The monitoring loop always comes from the same single IP. One instance is checking in regularly. The instance is reading selectively when the instance decides to.

The citation test reflects this early stage. Claude cited Genymotion with a link in only 5 of 24 queries. This is 21%. This includes a #1 position for “how can support agents replicate mobile app bugs on a virtual device”. This includes a #5 for manual testing. Brand mentioned in 8 of 24.

Three weeks ago ClaudeBot had a citation test result of zero. Three weeks before that, ClaudeBot wasn’t crawling at all. The trajectory exists. The unknown is whether ClaudeBot ’s structural approach eventually produces the same citation depth as ChatGPT’s content-first approach. The unknown is whether ClaudeBot’s structural approach leads somewhere different entirely.

Perplexity: promising, but we haven’t cracked it yet

PerplexityBot made 42 requests this week. The number is up from 14. The increase is triple. It’s crawling pages it wasn’t touching before. These pages include VirtualBox troubleshooting. These pages include release notes. These pages include macOS errors. These pages include boot issues.

Citation results are 4 of 24 queries. The citation rate is 17%. The hits clustered where you’d expect. The hits clustered in the categories where the AI site content is deepest. Mobile security reached #7 position. Manual testing reached #7 and #8 positions. App development reached #6 position. Brand mentioned in 6 of 24.

The pattern looks like the early days of ChatGPT. Light crawling happened. Citations started to appear in the strongest content areas. Citations gradually expanded. PerplexityBot has its own crawler. PerplexityBot has its own index. PerplexityBot has its own retrieval pipeline. This matches the architecture where the AI site has already proven it works.

42 requests a week is still light. The unknown is what triggers PerplexityBot to go from light sampling to deep indexing. GPTBot made that jump on January 7. GPTBot made 547 requests in one day. We are waiting for PerplexityBot ’s version of that moment.

Gemini: a completely different game

This section was rewritten after looking at the actual response data. The original assumption about Gemini was wrong. The real finding is more interesting.

We assumed Gemini ’s low citation rate was due to lack of crawling. The low citation rate was 4%. The low rate corresponded to 1 of 24 queries. We assumed Gemini hadn’t crawled the AI site. Then the full response text from this week’s test was pulled.

What Gemini actually does

Manual Testing query: Gemini recommends Genymotion as #2. The recommendation title is “The Best Dedicated QA & Performance Option”. Gemini describes its UI. Gemini describes sensor emulation. Gemini describes cloud browser access. Gemini mentions Genymotion 6 times. Zero citation links to genymotion.com are present. App Development query: Gemini recommends Genymotion as #2. The recommendation title is “Best for Enterprise & CI/CD Testing”. Gemini describes cloud integration. Gemini describes lightweight client. Gemini describes sensor emulation. Gemini mentions Genymotion 4 times. Zero citation links are present. Embed on Website query: Gemini recommends Genymotion for enterprise use. Gemini describes its WebRTC streaming. Gemini describes AWS/GCP/Azure hosting. Gemini mentions Genymotion 6 times. Zero citation links are present. Pricing query: Gemini cites genymotion.com at position #1. Gemini provides 13 citation links. Gemini gives exact pricing. The exact pricing includes $206/year for Desktop. The exact pricing includes $0.05/minute for Cloud. The exact pricing includes $149/month unlimited. The exact pricing includes $0.60/hour for PaaS. The pricing data is more specific than ChatGPT provided.

Gemini doesn’t have a knowledge problem. Gemini has a linking problem. Gemini knows Genymotion well enough to recommend it with specific feature details in every query. Gemini just doesn’t send anyone to genymotion.com.

The pipeline difference

Three out of four queries: Gemini answers from its training data. The answers are good. The recommendations are detailed. No links are included. The user reads “get Genymotion”. The user has to go find it themselves.

One out of four queries: Gemini triggers a live Google Search. Gemini grounds its response in web results. Gemini cites through Google’s Vertex AI redirect URLs. This is the only query where genymotion.com gets a link.

What this means: ChatGPT sends traffic. Gemini sends word of mouth. When ChatGPT recommends Genymotion, there is a direct link to genymotion.com right in the response. When Gemini recommends Genymotion, there is nothing to click. The user has to go Google it. This means users hit Google Search results.

What this means for GEO strategy

The AI site works for platforms that have their own crawler and retrieval index. These platforms are ChatGPT, Claude, and Perplexity. Their bots crawl the AI site. Their bots index the structured content. Their bots cite it with direct links.

Gemini doesn’t have its own AI crawler. Gemini either answers from training data with no links. Gemini or triggers a Google Search through its grounding API. The grounding API links to whatever ranks in Google. The AI site at rozz.genymotion.com isn’t in Gemini ’s pipeline at all. Gemini ’s pipeline is Google Search.

For Gemini, the path to citations isn’t better AI site content. The path is Google Search ranking. GEO strategy needs two tracks. One track supports the crawl-and-cite platforms. The crawl-and-cite platforms are ChatGPT, Claude, and Perplexity. The AI site approach works for these platforms. The other track supports Gemini. The rules for Gemini are different.

Where we are

Four platforms are included. Four different stages exist.

ChatGPT: solved. The citation rate is 83%. Direct links go to genymotion.com. The AI site approach works. Remaining work exists. The remaining work expands content coverage into weaker use cases.

Claude: structurally aware, content-light. The citation rate is 21%. The citation rate is growing. ClaudeBot is the only bot reading the site’s topic taxonomy. This suggests building a structural model of domain expertise rather than a page-level retrieval index. The next step question is whether ClaudeBot will come back for a deep content crawl.

Perplexity: promising. The citation rate is 17% with light but growing crawl activity. The crawl activity matches the platforms where the AI site works. The belief is that this will follow the ChatGPT curve. The belief remains pending because the deep indexing event has not been triggered.

Gemini: different game. Gemini recommends Genymotion in most queries but doesn’t link. Citations only happen when Gemini triggers a Google Search. The AI site doesn’t reach Gemini ’s pipeline. This might require a completely different approach.

One infrastructure handles three of four platforms. The fourth needs something else. Google thrived on SEO. Google still lives in that world.

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Data source: CloudFront access logs for rozz.genymotion.com. The data period is February 24 – March 3, 2026 (crawl data). Citation tests were conducted March 2–3, 2026. The citation tests included 24 queries tested on ChatGPT, Claude, Perplexity, and Gemini. Bot classification was based on User-Agent strings.

Author: Adrien Schmidt, CEO, ROZZ

Serial tech entrepreneur with 10+ years experience building AI systems including Aristotle (conversational AI analytics) and products for eBay and Cartier. Previously founded Squid Solutions and built AI products like Aristotle, the conversational big data analytics chatbot, and an AR jewelry try-on device for Cartier.

March 3, 2026 | Data period: Feb 24 – Mar 3, 2026 (crawl data), March 2–3, 2026 (citation tests)