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Imagine a potential customer enters your store - but no one sees them. They look around, check prices, compare products. And leave again without your staff ever noticing. That's exactly what's happening right now in thousands of online shops. New AI crawlers browse the web but hide themselves as completely normal users.
Besides clearly labelled crawlers such as GPTBot or ClaudeBot, there are AI-powered agents and browsers, such as ChatGPT Atlas or agent features that open websites on behalf of users. Such requests can use ordinary browser identifiers - Chrome on Windows, Safari on iPhone - and then carry no typical bot name in the user agent. Conventional analytics tools therefore struggle to distinguish them from human visitors. Looking only at declared bots shows just part of the AI traffic to your website.
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Classic crawler detection relies on the user agent. GPTBot and ClaudeBot identify themselves clearly, and several providers also publish the IP ranges of their crawlers. Agents that use a normal browser identifier cannot be captured this way. Server logs then show, for example, only "Chrome user from the US". Other characteristics can provide hints, such as originating networks, access patterns or technical properties of the request - but an unambiguous attribution is not possible in every case.
Knowing which AI systems visit your website enables more targeted optimization. Without this data, it remains unclear whether and how often AI systems fetch your content and which pages interest them most. This information helps prioritize a GEO strategy - for example, to check whether important pages are reached at all.
Roughly three groups can be distinguished. First, declared crawlers such as GPTBot, OAI-SearchBot, ClaudeBot or PerplexityBot: they name themselves in the user agent and can additionally be verified via IP lists published by the providers. Second, user-initiated fetches such as ChatGPT-User or Perplexity-User, which load a page because a person asked for it in the chat - these are usually labelled as well. Third, agents and AI browsers that use an ordinary browser identifier. This third group is the hardest to attribute; only indicators such as originating network, timing and access patterns help, and misattribution is possible.
Without extra software, you can get a first overview from your server logs. Filter requests by known AI user agents such as GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot and PerplexityBot. Then check whether the IP addresses match the provider's published ranges - spoofed user agents are common. What matters next is which pages are fetched, with which status code and how often. If important pages show error codes or redirect chains, that is a concrete starting point. Many hosting providers offer log downloads in their customer area.
Even if not every AI request can be attributed, everyone benefits from a website that is easy to read. Deliver important content in the HTML instead of loading it later via JavaScript. Keep load times short and avoid redirect chains. Check whether bot protection or CDN settings unintentionally lock out known AI crawlers. And make sure prices, services and contact details exist as text. These measures improve readability for declared crawlers, for agents with browser identifiers and for human visitors alike.
Not every AI request identifies itself as a bot. Evaluating additional characteristics alongside declared crawlers gives a much more complete picture. Beconova combines several detection layers for this - complete detection of all AI requests is, however, technically not possible.
Check GEO Score for freeMarvin Malessa
Founder, Beconova
Founded Beconova in Germany in 2025 to help shops and service businesses become visible in AI search engines. Writes about GEO, AI visibility, and the future of search.
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