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How aisle measures AI visibility

Written for humans. No score without a method behind it.

What we measure

For each product category we maintain a library of real buyer questions (“best air purifier for allergies?”, “best running shoes under ₹5,000 in India?”). Every week we put those questions to five AI surfaces — ChatGPT, Claude, Gemini, Google AI Overviews, and Google AI Mode — and record which brands each answer recommends.

Why we ask the same question many times

AI answers vary run to run: the same question can mention your brand once and skip it the next time. A single check is noise. We ask each question multiple times and report your visibility as a percentage with a 95% confidence range. If two numbers’ ranges overlap, we say so instead of pretending one is bigger. We only alert you when a change is statistically real.

Markets are never mixed

A US shopper and an Indian shopper get different AI answers, so we sample each market separately — US questions with US locations and desktop Google, Indian questions with Indian phrasing (₹ price points, local brands) and mobile-first Google, which is how India actually shops. Your US number and your India number are two different facts, and we never average them.

What we honestly can’t measure

Where the homepage statistics come from

Questions?

Ask us anything via the early-access form on the homepage — methodology questions get answered first.