How to investigate an AI visibility gap

Use this workflow when competitors appear in AI answers and your brand does not. It helps you move from a dashboard gap to a specific, evidence-based content or information improvement.

1. Check the business context

Open Website Settings and review the market, language, topics and competitors. A restaurant in one city should not automatically use national category questions as its only success measure. Choose questions that reflect real customer decisions.

2. Fix the comparison scope

Open AI Visibility. Record dates, model/platform selection and whether the view is branded or unbranded. Compare like with like. A request explicitly naming your business tests a different behaviour from a general recommendation question.

Read mentions, citations, sentiment and visibility as distinct measurements. A brand may be mentioned without its website being cited, and a cited third-party page is not necessarily an owned website citation.

3. Inspect the underlying question

Use a competitor gap or open Prompt Research. Review the exact wording, topic and available run history. If the detail screen has no runs in the chosen window, do not treat that as proof that the brand was absent from an actual response.

Check individual platform results, cited sources and the date of each run before summarising a trend. Record when the overview and detail views do not reconcile so that the data can be checked.

4. Form a specific hypothesis

Ask what verified information is missing, unclear or difficult to find. Examples might include an accurate menu, explicit service-area information or a clear description of a cuisine speciality. Validate that the business really offers what the proposed content would claim.

A source appearing in an answer may be useful research evidence, but it does not guarantee that copying its wording or acquiring a link there will make your brand appear.

5. Implement and monitor carefully

Prepare a reviewed draft in Content Writer, manage the work in Task Manager, and record the actual deployment in Annotations. Recheck comparable prompts, models and dates over multiple runs after implementation.

AI answers vary. One newly positive result is an observation, not proof that a content change caused it or that the brand now ranks consistently across AI products.

Worked example

A prompt asks for a South Indian restaurant in Southampton. Inspect which businesses and sources appeared, verify whether the target business fits the request, and review whether its relevant location, cuisine and menu information is accurately represented online. Prioritise correcting an actual information gap rather than adding generic “AI optimised” text.

The outcome is a documented hypothesis, a factual improvement and a repeatable comparison—not a promised citation or recommendation.