People also ask
In practice
Large models learn from snapshots of the web, and Common Crawl — hundreds of billions of pages collected over the years — is a major ingredient in many of them, alongside licensed and proprietary data. For a brand this creates a second, slower visibility layer: a model that saw your site in training can recommend you with web search switched off, from memory. The practical implications are unglamorous. English dominates the corpus overwhelmingly, so non-English markets need genuinely valuable English versions of key pages to be represented in the next training run, not machine-translated shells.
Blocking the CCBot crawler in robots.txt removes a site from that pipeline — a defensible licensing stance, but a deliberate exit from the training-data path, and one to take knowingly rather than by copy-pasted robots files. Access matters more than submission: there is no form to fill in, only a crawlable, valuable site that gets linked and pinged enough to be picked up, and then patience, because training runs happen on the model owner’s schedule. Distinction worth keeping: training-data presence is durable but stale — a model can recommend a product that has since changed — while retrieval reflects the live web.
Sophisticated buyers test both: the same questions asked with search off reveal memory; with search on, retrieval. A brand visible in neither layer is starting from zero wherever the buyer asks.
See also: Training data presence vs retrieval, AI crawler access, GEO.
Checklist: Link Building for GEO.
Related service: Brand mentions.
