Methodology

How InView Measures AI Visibility

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.

10 buyer questions ChatGPT · Claude · Perplexity Fully automated ~2 minutes
01UnderstandWe read your site to understand what you offer and who you serve.
02AskTen realistic buyer questions are built for your category.
03TestEach is put to ChatGPT, Claude and Perplexity as a fresh test.
04MeasureEvery response is recorded and judged in real time, with no human review.
05CompareYour position is set against every provider that appeared.
06ImproveFindings point to what the evidence suggests is worth investigating.
07RerunThe same questions, platforms and scoring rules, measured again.

Independent tests

Each question is run independently, without conversational history from previous tests. Unbranded questions do not name the business being audited.

Competitive landscape

We show which businesses are being surfaced most often, how often each appears, and the customer-intent areas where the audited business is appearing or missing: category, problem, buyer requirement, use case and comparison questions.

Recommendation Rate
17%

How often was the business recommended? The percentage of valid customer-decision tests in which the audited provider was recommended.

Example figure · Free scan
Share of Recommendation
8%

How much of the recommendation landscape did the business capture? Your appearances divided by all provider recommendation appearances. Each provider counts at most once within an individual answer.

Example figure · Free scan
Brand Score
90

How well does AI understand and represent the business? Separate branded questions assessed on Accuracy, Confidence and Evidence. An InView proprietary tracking measure, not an industry-standard score.

Example figure · Free scan

A baseline establishes a starting point.

For a comparable future measurement, the same questions, platforms and scoring rules should be used. Material methodology changes are versioned rather than silently changing the comparison.

Baseline → Identify gaps → Improve → Rerun → Measure movement ↺

The limits of this measurement, stated plainly.

01

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.

02

We don't claim every customer asks the exact questions we test. The set is designed to be realistic and consistent, not exhaustive.

03

We don't claim results will never vary. AI outputs are probabilistic and change with model updates, sources, geography and timing.

04

We don't claim AI visibility replaces SEO. It is another layer of visibility alongside the work you already do.

05

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.

Run the measurement on your own business.

An InView report is a structured snapshot of the defined tests at the stated time, not a permanent ranking or guarantee.

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