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Start with questions people actually ask your business, group them by the decision they support, and turn each group into a small set of test prompts. Keep observed questions separate from hypothetical variations. A prompt list is a test plan; it is not a search-volume report.
Collect questions with their context
A useful question record includes the wording, where it came from, the buyer’s constraints and the date. Use permissioned customer research, support themes and anonymized sales notes. Avoid putting personal or confidential material into a public content brief.
“Does it integrate?” is too vague. “Can our operations team connect it to the accounting tool we already use?” names a decision. Preserve that difference when you remove identifying details. Count repeated observations only when you can inspect the underlying records.
Build one row per decision
| Field | Example |
|---|---|
| Question | Can I get an appointment after work? |
| Context | Local customer; weekday evening required |
| Decision | Whether this provider is available |
| Evidence needed | Published hours and live appointment options |
| Source page | Hours and booking page |
| Provenance | Hypothetical example; demand unmeasured |
This row is intentionally more specific than a keyword. It tells an editor what to verify and a product owner which action must work. It also makes a missing fact visible before anyone writes an article.
Vary one meaningful constraint at a time
Test a baseline question, then change the location, integration, budget or availability requirement. Keep the other constraints stable. That makes the difference between two observations easier to explain.
For example, compare “appointment after 6 p.m. in Miami” with “appointment on Saturday in Miami.” Those prompts test availability. Adding five unrelated adjectives creates a different scenario and makes it harder to identify the missing source fact.
Keep navigational prompts that name your business separate from category prompts that do not. Finding a named company is a different task from choosing among providers.
Keep a reproducible observation record
Record the assistant, interface, date, market, full prompt, returned answer and linked URLs. Note whether web search was available. Repeat a small fixed cohort over time rather than expanding the test set whenever you dislike an answer.
If an answer does not appear, mark the observation unavailable. If the assistant provides no link, record a mention separately from a citation. A generated answer is evidence of that run; it is not proof that every buyer sees the same result.
Turn the gap into a content task
A gap becomes actionable when you can name the missing fact, its owner and the public page that should explain it. “Improve AI visibility” is not a writing brief. “Publish evening hours and link the booking form from the service page” is.
Use a priority queue to choose the next task. Follow the citation measurement method when you retest. Do not describe a prompt generated by a model as customer demand unless you have independent evidence.
Sources and editorial scope
Published October 20, 2026. This is Arrow AI’s editorial method. Examples and scores are illustrative, not measured demand, customer results or AI ranking factors. The linked documentation provides platform context.
The Arrow read
Give your visibility work a concrete brief
Use Arrow AI’s free GEO audit as a starting point for investigating your public business information. Add your own customer questions to the review, then connect each verified gap to a source page and a responsible owner. The result is a useful improvement queue with clear reasons for each task. Run the free GEO audit.