Direct questions · No. 01 / 31
1. What is AI search visibility, and what should we actually measure?
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For this research desk, AI search visibility means whether a business is mentioned, cited or recommended in answers to relevant buying questions. Measure those outcomes separately, alongside factual accuracy and any observable commercial response.
This distinction is consistent with research that separates discoverability, citation, use of information and economic outcomes rather than compressing them into one ranking. A July 2026 research survey also cautions that evidence for improving one stage does not automatically establish improvement in another. (arxiv.org)
Use the following operational definitions in your own reporting:
| Measure | What counts | What does not follow from it |
|---|---|---|
| Brand mention | The answer names the correct company or product | The answer endorses it |
| Owned-site citation | The answer links to a page you control | Your product is recommended |
| Third-party brand evidence | A cited external page discusses your business | The assistant relied on that passage |
| Explicit recommendation | The answer presents your product as suitable for the stated need | It is suitable for every buyer |
| Qualified recommendation | The recommendation includes conditions or limitations | The conditions are necessarily accurate |
| Accuracy | Checkable statements match dated, approved evidence | The entire answer is reliable |
| Commercial response | A recorded visit, enquiry or customer-reported discovery event | AI visibility caused incremental revenue |
An answer can cite your research while recommending a competitor. It can also recommend your product without linking to your website. Your scoring rules should accommodate both cases rather than forcing every observation into a single visibility score.
Sources cited on this page
- arxiv.org arxiv.org/abs/2607.14035