Why We Built TakeScout
Bootstrapped and building the kind of tool tourism marketers actually need.
Travelers are already asking AI where to go.
More travelers are turning to AI assistants — ChatGPT, Claude, Gemini — to plan trips: where to eat, where to stay, what to see. Those assistants are already shaping which restaurants get visited, which hotels get booked, and which attractions get skipped.
Most destinations and tourism organizations have no visibility into any of this. They don't know what AI is telling travelers about them, whether it's accurate, or how it compares to what a neighboring destination is being told.
Our approach
We don't guess, and we don't ask once. TakeScout repeatedly asks AI assistants the same kinds of questions real travelers ask — about fine dining, family trips, hidden gems, winter travel, and more — and tracks what comes back over time.
That repetition matters. A single AI answer is a snapshot. Asking the same question multiple ways, across multiple models, over time, is what turns a snapshot into a pattern — a stable "canon" of what AI consistently recommends, versus what only shows up once and never again.
What we publish
For each destination we track, we publish:
- Which places AI recommends most consistently, by category and by traveler intent (romantic trips, family travel, budget travel, and more)
- How consistent those recommendations are across different phrasings of the same question
- Plain-language findings — the patterns worth knowing, not just raw rankings
This content is free to read. Our goal is to give tourism boards and destination marketing organizations (DMOs) a clear, honest look at how AI is already representing their destination, before they ask us for anything more detailed.
Where we're going
We're starting with one destination and expanding from there — more cities, more AI models, tracked over a longer period of time. The goal is a running record of how AI talks about a place, not a one-time report.