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In practice
Common Crawl crawls the web in multi-billion-page snapshots released roughly monthly, and model builders use these snapshots — heavily filtered — as a backbone of training data alongside licensed books, code and proprietary scrapes. The snapshot view of a brand is therefore a slow mirror: it reflects the web as of some past crawl, and a model trained on it will not know about last month’s relaunch.
Checking presence is direct: search the index for the domain, or query a model with web search disabled and see whether it describes the company at all — the second test is the one that matters, because filtered training pipelines may use the crawl without treating every page as important. Levers over inclusion are limited but real. Do not block CCBot in robots.txt if training-data presence is wanted — a block is a deliberate exit from that path and worth a conscious decision rather than a copied robots file. Get linked from pages that crawlers traverse often; crawl discovery follows links.
Publish the substantive English version of key material, because English dominates the corpus by an overwhelming margin and machine-translated shells add nothing a filter would keep. And keep the fundamentals clean — pages that render without JavaScript, real content rather than stubs, stable URLs — because filters reward readable, substantial pages. None of this replaces retrieval work; it complements it — memory makes a model recommend you unprompted, retrieval makes it cite you today, and serious brands want both.
See also: AI crawler access, LLM optimisation, LLMs.txt.
Checklist: Link Building for GEO.
Related service: Brand mentions.
