Guests plan trips by asking ChatGPT, Gemini and Google's AI Overviews where to go, and the destinations they name win the shortlist. We map how AI describes a destination, engineer it to become the cited answer, and track its share of the AI conversation, built for destinations.
A guest choosing between the Maldives, the Cook Islands and the Whitsundays now opens ChatGPT or Google's AI Overviews before a search engine. Whichever destination the model names makes the shortlist; the rest disappear before the guest reaches a website.
This is a gap the old marketing dashboard was never built to show. A destination can post strong paid and organic numbers and still be missing from the AI answer that shapes the dream.
Ask an AI engine where to go, and a destination can be the single recommendation, one of several names, a passing mention, or missing. Where it sits, and how it is described, decides whether it makes the trip.
Most destinations only find out by accident. We measure it deliberately, engine by engine and market by market, so the picture is real rather than a guess.
When a guest asks a model where to go, one destination gets named and the rest vanish. We built the system that makes yours the one it names.
We map how every major AI engine describes a destination today, engineer the content, sources and signals that move it from absent to cited, and track its share of the answer over time. It runs now for destinations across Australasia.
Teams elsewhere have raised venture funding to build toward this. We already run it.
How every major AI engine describes the destination, its sectors and its competitors, and where the gaps and errors sit.
The structured content, sources and signals that move a destination from absent to cited when guests ask.
Share of voice and share of model across engines and markets, so a destination knows where it is winning the answer.
A destination sells nothing directly, competes with its own operators, and is accountable for the whole region's answer. Our model measures the twelve outcomes a destination is judged on and covers all thirteen reasons to visit, across every stage from dreaming to booking.
The same question returns different destinations depending on where it is asked, so we run the whole library market by market. A destination sees its answer in each source market that matters.
The outcomes a destination is accountable for, from destination selection and length of stay to spend, seasonal spread and reputation.
Food and wine, ski, adventure, nature, wellness and more, each covered to depth so no sector dominates the answer.
From first inspiration to booking and beyond, where different engines and prompts decide the shortlist.
The library re-run from each source market, because the answer changes with where the guest is asking.
We build a structured prompt library, the instrument that tests how a destination appears across topics, audiences and phrasings. Every run lands in a BigQuery warehouse the destination owns and reads in Journey Based Metrics, so AI visibility sits next to paid, organic and bookings.
We stitch in earned media through Meltwater: share of voice, reach and sentiment against the competitor set. That coverage is what AI engines read, so brand visibility and AI visibility rise together.
A selection of client outcomes. Every figure is drawn from the client's own analytics.
It begins with a clear read of where the destination stands in AI answers today, and moves to the work that makes it the answer.
A full read of how AI engines describe the destination today, by sector, market and engine.
The gaps and errors that cost the most visibility, ranked, with the reason for each.
We build the content and signals that make the destination the answer, and track its share of the AI conversation live.