FIELD GUIDE / 5 min read

How to evaluate your AI search visibility

Build a repeatable baseline without treating every answer as a ranking.

Define a useful question set

Collect questions from customer conversations, sales objections and support requests. Include discovery, comparison and suitability questions. Document market, language and location. Keep the set stable enough to compare over time, and record any changes.

Keep a transparent observation log

For each test record the question, platform, date, whether search was used, the brands named and any source links. Save the answer or a screenshot for review. Repeated runs reveal variation that a single screenshot can hide. Manually sampled answers describe that sample, not all users' experience.

Separate the metrics

Mention rate is the fraction of sampled answers naming a brand. Citation rate counts answers linking to a defined source or domain. Competitor comparisons need the same question set and conditions. Referral visits and lead outcomes belong in a separate analytics view with clear attribution limits.

Decide what to change next

Review inaccurate descriptions, missing relevant pages, unanswered questions and credible sources competitors appear in. Prioritize changes that also improve the customer experience. Recheck after implementation rather than assuming a correlation proves the change caused an answer.

Sources & further reading

These guides distinguish practical recommendations from platform guarantees. Start with the platforms’ own documentation.

Google: AI features and your website ↗Google: creating helpful, reliable, people-first content ↗

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