Routes bring the people, hotels hold them, venues and events give them a reason to come, and paydays, holidays, weather, and sentiment move the whole thing week by week.
Until now every part was run by a different team looking at a different screen. The airline sees its routes. The hotel sees its rates. The venue sees its calendar. The government sees arrivals, six months late. Each one optimises what it can see, and each decision changes the return on the others.
The signals exist. They have never been in one model.
| Product | Your question | You get | What it changes |
|---|---|---|---|
| Demand137 | Which date for the next event? | Candidate weekends scored and ranked, binding constraint named | You pick the date with the fewest forces against it |
| Demand137 | Are ticket sales on pace? | Sales against archetype pacing, break-even gap, forecast finish | You act while there is still time |
| Demand137 | What should we charge? | Sell-through by segment, price premium exposure | Prices set on evidence, not last year plus ten percent |
| Demand137 | Which rights to renew? | Portfolio ranked by demand and exposure per slot | You renew the ones that earn their slot |
| Demand137 | Which markets and routes? | Inbound by market and route, access ceiling as the cap | The case and the result use the same spine |
| Demand137 | What is the mood in the market? | Sentiment and search by market and language, shift detection | You see the movement before it reaches the booking curve |
| Demand137 | How far will the event's reach go? | Forecast reach, with the inferred and observed split shown | A projection is never presented as a measurement |
| Demand137 | What happens if we do nothing? | The base case as the reference, with the counterfactual stated | The cost of waiting priced alongside the cost of acting |
What Demand137 holds
Every airport and route, every hotel market with its supply and rate, and every venue with its capacity. Bars, restaurants, and drive-time catchments and isochrones for our locations.
What that infrastructure has already carried. Flight demand by route and origin market. Room nights by market. Attendance by event. The observed record of how the system actually behaves.
What moves through the system, and what moves it. The event spine: every event, its class, its dates, its history, and what it drew. Paydays and public holidays by country. Weather and disruption. Competitor dates. What people are searching for, by market and language. What they are saying, from social listening. What is being reported, from the news.
Billions of data points sit in the same time index as the flights, the rooms, and the venues.Bookings tell you what happened. Search, social, and news show what is coming next.
Machine learning
A trained model family on real labels, in production, with lineage:hundreds of thousands of paired hotel-rate observations and flight-fare observations as the first training sets, event attendance from the catalogue as the second. Training is reproducible: run as three separate processes, it produces identical artefacts.
Rolling-origin backtests across at least fifty events per class, reported as interval coverage and pinball loss against the naive baseline. Each edition’s measured impact in Signal137 becomes the prior for the next edition’s forecast in Demand137, automatically, on the same spine.
International visitors to the United States fell 4.2% in 2025, the first annual decline since the pandemic, while worldwide travel grew. The spending did not disappear. It moved. Five economies are absorbing most of it, and the shift now looks structural.
Oman has announced plans for a high-altitude destination at Jabal al Akhdar, combining sports training, wellness, and tourism at 2,400 metres. It is the kind of project a Gulf government can commit to at once, and the kind that lives or dies on a demand case nobody has yet published.
International arrivals to the United States fell 4.2% in 2025 while worldwide travel grew about 4%. Living Lab’s displacement model puts the forgone spending at roughly US$50bn, and about US$10.6bn of it within reach of five economies. Each is limited by a different constraint.
Most destinations run near capacity for part of the year and well below it for the rest. A visitor added in the peak displaces one already there. A visitor added in the shoulder fills an empty room and is served by staff who would otherwise be idle. Almost no destination runs the calculation before fixing a date.
We turn messy event and tourism data into decisions that help communities grow. Bring curiosity and rigour. We will hand you questions nobody has answered yet.
