How we turn real buyer questions into a consistent view of where your brand appears in AI search, who gets recommended instead and where you can improve.
AI answers can change between platforms and over time. InView measures patterns across a defined set of customer questions rather than relying on a single search.
Each question is run independently, without conversational history from previous tests. Unbranded questions do not name the business being audited.
We show which businesses are recommended most often, how often each appears, and the types of question where the business appears or is missing, such as feature, category, use-case, comparison and problem-led questions.
Does AI recommend the business? How many scorable answers recommended the business, shown by platform and by type of question. An answer that names no business, or couldn't be fully analysed, isn't counted.
Fictional example (Saltbush Sofas), illustrative onlyWho else gets recommended? The number of answers that recommended each business, counted once per answer, and the questions each business wins.
Fictional example (Saltbush Sofas), illustrative onlyDoes AI know who the business is? Whether each platform describes the business correctly when asked by name and with more context. Quotes are shown word for word from answers about the business.
Fictional example (Saltbush Sofas), illustrative onlyEach report is a snapshot of the defined tests at the stated time. Material methodology changes are versioned rather than silently changing results.
Current methodology: version 3 (November 2026). Each scan records the version it was measured under, and earlier reports keep the results they were measured with. Version 3 made four changes:
We don't claim to know a secret AI ranking algorithm. AI platforms do not expose a complete explanation of why a provider was recommended.
We don't claim every customer asks the exact questions we test. The set is designed to be realistic and consistent, not exhaustive.
We don't claim results will never vary. AI outputs are probabilistic and change with model updates, sources, geography and timing.
We don't claim AI visibility replaces SEO. It is another layer of visibility alongside the work you already do.
We don't claim correlation proves causation. We distinguish between what we observed, what the evidence suggests, and what is worth testing.
Businesses named in reports reflect providers surfaced in the measured third-party AI outputs. Appearing more frequently does not mean InView has independently determined that provider is objectively better.
Payment never affects measurement. A commercial relationship with InView does not change how a provider is counted, scored or included, or which competitors appear in the underlying results.
An InView report is a structured snapshot of the defined tests at the stated time, not a permanent ranking or guarantee.