Glossary

What is Training Data?

The corpus a model learns from. What it says about your brand — unprompted, without retrieval — was decided by this data.

Definition

Training data is the text corpus a language model learns from: web crawls, licensed content, books, code, forums. Everything a model 'knows' unprompted about your brand — what you do, who you compete with, whether you're worth recommending — is a statistical residue of how the corpus talked about you.

Why it matters

Training data is the slow, deep layer of AI visibility. You influence it by being consistently, accurately, widely described across the surfaces crawlers ingest — reviews, press, documentation, communities, Wikipedia-tier references — before the next training snapshot. Brands well-represented in training data get mentioned even in ungrounded answers, with no retrieval required. It's PR with a compile step: everything published about you now is a vote in every future model.

Frequently asked

Can I get my content into training data?

You can't submit it, but you can be crawlable by training bots (GPTBot, Google-Extended, ClaudeBot) and ensure third-party surfaces describe you accurately — models weight corroborated, widely-repeated information.

Can I remove my brand from training data?

Blocking training bots stops future collection but doesn't unwind past training. Corrections propagate through model updates over months — another reason to keep the retrieval layer (which updates instantly) accurate.

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