We measure what ChatGPT, Perplexity, and Google answer when someone asks about your category. With data, not opinions: real queries, saved answers, and your share of mentions against the competition.
We audited a bakery in Chile's Valparaíso Region with four locations, a 4.6 rating, and 372 reviews. We measured 12 queries across four AI engines and saved all 64 answers.
The pattern: when the customer already knows what they want, the brand shows up. When they ask who's the best, it disappears. The bakery next door, with fewer reviews and a lower volume score, gets the recommendation.
Market tools measure Google rankings. None of them tell you what ChatGPT says when asked about your industry. We query the real engines and hand you the raw answers.
Many stores only render their catalog after the browser builds the page. For GPTBot, ClaudeBot, and PerplexityBot, that catalog simply doesn't exist. We measure it page by page.
In the case study, of the 39 domains cited only 5 appeared in more than one engine. Optimizing for Google doesn't get you into Perplexity. Each of the four has to be measured separately.
A PDF report with the current state: what's working, what isn't, and your share of mentions measured across four AI engines. Every finding backed by evidence: the exact URL and the observed data.
Tasks prioritized by dependency, each with an owner, an effort estimate, and a verifiable acceptance criterion. Separating what you can fix yourself from what depends on your platform.
The specialty reports, the screenshots, and the unedited answers from every engine. All reproducible: the same measurement repeats at 60 and 120 days to show progress.
The answer is measurable. We give it to you with data.
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