What is Five Blocks’ AI reputation methodology?
Five Blocks applies its Track / Analyze / Impact framework to AI: track what the engines AIQ covers say across models, sources, and time; analyze the sources and themes driving the picture; then fix it at the sources the engines actually read, not by prompting the engines.
Our AI reputation methodology is the same Track / Analyze / Impact framework we built for the Google era, applied to the AI layer. We measure what the engines are saying, find the sources shaping that picture, then fix it at those sources rather than at the answer people see.
The three phases, applied to AI
- Track. Using AIQ, we capture what each of the engines AIQ covers, ChatGPT, Gemini, Copilot, Perplexity, Claude, Grok, Google AI Overviews, and Google AI Mode, says about the client and named peers: the sources each engine cites, the sentiment and themes, and how they move over time.
- Analyze. We find the leverage points: which sources drive which framings, where the engines disagree with each other, where peer comparisons reveal an opening, and which interventions will move the picture with the least effort.
- Impact. We do the hands-on work at the sources themselves, Wikipedia, Wikidata, owned content, authoritative third-party coverage, and structured entity signals, because those are what the engines actually read.
Why we work at the source, not the prompt
You can’t fix what AI says by prompting the engine or telling it it’s wrong. It doesn’t remember what you tell it, and it rebuilds every answer fresh from the sources it trusts. The only lasting way to change an answer is to change what those sources say.
Last reviewed: 19/05/2026
