Destination Intelligence
Destination intelligence, defined.
Destination intelligence is structured, AI-readable tourism data that lets AI systems discover, understand and recommend the businesses and experiences inside a destination, combining a knowledge graph of verified supplier data, distribution of that data to AI systems, and measurement of how those systems actually answer.
The four layers
Destination intelligence is not a product a destination installs. It is four layers, each of which fails on its own: data nobody collected, structure nobody agreed, distribution nobody set up, and measurement nobody ran.
1. Collection
Verified data from the suppliers themselves, not scraped, not inferred, and not limited to whoever already has a good website.
2. Structure
An agreed taxonomy and data model, schema.org markup, and one canonical identifier per entity so the same supplier is one thing everywhere.
3. Distribution
Publication in the forms machines read: structured data on the pages, an llms.txt, robots rules that actually admit assistant crawlers, and direct feeds through MCP servers and APIs.
4. Measurement
Traveller questions run against the major AI assistants every week and scored, against a Day 0 baseline. Without this the other three layers are an act of faith.
Destination intelligence vs destination marketing
Destination marketing produces content for people to be inspired by. Destination intelligence produces data for machines to answer from. A campaign page persuades a traveller who already found the destination; a structured supplier record decides whether an assistant mentions it at all. The two are complementary: marketing shapes what the destination means, intelligence decides whether it is reachable in an AI-led planning journey. But they are not substitutes, and a marketing budget spent on more content does not produce more intelligence.
Destination intelligence vs tourism business intelligence
Tourism business intelligence looks backwards at people who already arrived: arrivals, spend, length of stay, origin markets, dashboards for the board. Destination intelligence looks at the data an AI system needs in order to recommend the destination to someone who has not decided yet. One is a reporting problem about visitors you had; the other is a data-supply problem about visitors you may never hear about, because the recommendation that excluded you left no trace in your analytics.
Why it became urgent
Around 62% of travellers have already used AI to plan or book travel, and most begin planning without a single destination decided. That gap is the whole opportunity: when a traveller asks an assistant where to eat in a city, the answer is assembled from whatever is readable, and the independent operators that make a destination distinctive are usually the least readable things in it. The destinations that close the gap first do not merely rank better. They are the ones with anything to say.
How a destination builds it
In sequence, and starting with a number. Baseline what assistants say today; map the ecosystem and agree which cohort matters most; collect from suppliers on the channels they answer on; structure the result to an agreed taxonomy; publish it in machine-readable form; then re-run the baseline and see whether the answers moved. Each step produces a document or a dataset the destination keeps, which is what separates this from a subscription.
Common questions
Answers, in the body of the page.
- What is destination intelligence?
- Destination intelligence is structured, AI-readable tourism data that enables AI travel planning systems to discover, understand and recommend the local businesses and experiences within a destination. It is built from four layers: verified supplier data collected from the suppliers themselves, an agreed structure with stable canonical identifiers and schema.org markup, distribution to AI systems through machine-readable publication and feeds, and continuous measurement of how assistants actually answer traveller questions about the destination.
- How is destination intelligence different from tourism business intelligence?
- Tourism business intelligence reports on visitors who already arrived: arrivals, spend, length of stay, origin markets. Destination intelligence concerns the data an AI system needs to recommend the destination to a traveller who has not decided yet. The distinction matters practically: a recommendation that excluded your destination leaves no trace in your analytics, so business intelligence cannot detect the loss that destination intelligence exists to prevent.
- Who is responsible for destination intelligence within a destination?
- In practice it sits with the DMO or tourism authority, because it concerns how the destination is represented rather than how any single supplier is. It cuts across marketing, which owns representation, and data or IT, which owns systems, which is why it stalls when treated as purely one or the other. Governance stays with the destination: approval of what is published, provenance on every field, and an audit trail.
- Can a destination build destination intelligence itself?
- Yes, and some of it should be built in-house: the taxonomy, the governance rules, and the decisions about which suppliers matter are all destination decisions. The hard parts to build alone are reaching thousands of small suppliers on the channels they actually answer, and measuring AI answers consistently enough that week-over-week movement means something. Those are where most in-house efforts stop.
- How is AI visibility for a destination measured?
- By running a fixed set of realistic traveller prompts against the major AI assistants on a schedule and scoring the answers for whether the destination appears, whether the suppliers named are real and accurately described, and whether the answer is favourable. Holding the prompts and the schedule constant is what makes the result comparable; measured against a Day 0 baseline taken before any work began, it shows whether the programme changed anything.
Where we start
Find out what AI says about your destination today.
We read your site the way an AI crawler does, six checks and no opinion in any of them, and capture a Day 0 baseline of what assistants currently say. Before any programme is committed to.