Find the citation gap between you and competitors

The useful way to approach AI search is evidence first: define the buying question, observe which sources shape the answer, then improve the information buyers and retrieval systems can verify.

Start with a decision, not a vanity query

A broad prompt such as “tell me about our brand” reveals little commercial intent. A measurable prompt describes a buyer, job, constraint and market. Keep wording frozen between scans so movement has meaning.

Separate mention, recommendation and citation

A brand can appear in an answer without being recommended. It can be recommended without its own domain being cited. Track these as different observations. The source URL often exposes the most actionable gap: a missing comparison, proof page, research asset or third-party validation.

Connect GEO work to the SEO system

Clear site architecture, crawlable pages, specific claims, internal links, original data and reputable external mentions help both conventional discovery and grounded AI answers. GEO is not a replacement for SEO; it is a new evidence surface in the same buyer journey.

A practical workflow

1. Collect 10–15 real buyer questions from sales calls, search data and competitor research.
2. Record answers, positions and citations across explicit surfaces.
3. Group missed prompts by buyer job rather than model.
4. Create or improve the smallest source that resolves the evidence gap.
5. Re-run the same prompts after the source has been crawlable long enough to be discovered.

Avoid false precision

No tool can promise a universal “ChatGPT ranking.” Results vary by surface and context. Treat the score as orientation, keep the underlying rows, and label provider failures as unmeasured.