The Core Problem: Why the Tourism Data Gap Exists
The tourism data gap exists because no single traditional dataset shows the full visitor journey.
Most destinations can partially answer:
- Is the place busy? (footfall)
- Are beds full? (hotels)
- Did visitors say they liked it? (surveys)
But they cannot reliably connect:
- Where visitors stayed
- How they moved through the destination
- What economic impact they generated
Shortterm let, mobility, and spend data each address a different blind spot. Combined, they provide end-to-end tourism intelligence.
Each Dataset Closes a Different Part of the Gap
Short-Term Let (STL) Data Closes the “Where did visitors stay?” Gap
What STL data shows:
- Volume and distribution of tourist accommodation outside hotels
- Occupancy, availability, and seasonality
- Length of stay patterns
- Spatial pressure on neighbourhoods
Why this matters?
Traditional tourism data undercounts visitors who don’t use hotels and misses whole segments of the visitor economy and cannot explain accommodation pressure or compliance issues
What Short Term Let data enables:
- Visibility of the hidden accommodation market
- Accurate estimates of overnight visitor volume
- Evidence for regulation, policy, and licensing decisions
- Better understanding of seasonal and localised impacts
Short Term Let data turns “unknown stays” into measurable tourism demand.
Mobility Data Closes the “Who visited, where they came from, and how they behaved” Gap
What mobility data shows
- Unique visitors (not just activity)
- Origins (domestic and international)
- Dwell time and frequency
- Movement across places
- Visitor vs local behaviour
Why this matters?
Without mobility data, footfall inflates activity but hides people, day visitors are invisible and visitor journeys are fragmented
What mobility data enables:
- True visitor volumes, including day trippers
- Clear origin market insight
- Understanding of visitor behaviour over time
- Measurement of event, campaign, and seasonal impact
Mobility data turns movement into meaning.
Spend Data Closes the “What was the real economic impact?” Gap
What spend data shows
- Visitor expenditure by category (retail, food, attractions)
- How spend is distributed geographically
- Spend linked to visitor presence
Why this matters?
Traditional economic estimates rely on outdated multipliers are disconnected from actual visitor behaviour and lack credibility under scrutiny
What spend data enables?
- Direct measurement of visitor value, not just volume
- Understanding of high-value vs high-volume tourism
- Evidence for funding bids and investment cases
- Alignment of tourism with economic development strategy
Spend data turns visitors into validated economic impact.
Why They’re Most Powerful Together
Individually, each dataset improves tourism insight. Together, they close the tourism data gap entirely.
How the datasets connect
| Question | Dataset |
|---|---|
| How many visitors came? | Mobility |
| Where did they stay? | Short-term lets |
| How long did they stay? | STL + Mobility |
| Where did they move? | Mobility |
| What did they spend? | Spend |
| Which visitors drove value? | Mobility + Spend |
| Where was pressure felt? | STL + Mobility |
| Did an event or campaign work? | Mobility + Spend |
What This Unlocks for Destinations
By combining Short Term Let, mobility, and spend data, destinations can:
- See the full visitor journey: from arrival → stay → movement → spend → return
- Move beyond proxies: No more relying on Footfall as a stand-in for tourism, surveys as a stand-in for scale and models as a stand-in for impact
- Make confident, defensible decisions: Evidence-backed funding submissions, targeted destination marketing, balanced growth and regulation, smarter event and infrastructure planning
From Fragmented Metrics to Decision-Grade Insight
Old approach
- Disconnected datasets
- Annual, backward-looking reports
- Activity without value
New approach
- Integrated insight
- Continuous understanding
- People and value-based decisions
How to use in Practice
- Policy: Regulation, compliance, housing balance
- Tourism strategy: Market prioritisation and campaign ROI
- Economic development: Investment justification
- Place management: Pressure, capacity, and seasonality
- Reporting: Credible, repeatable insight year after year
Short-term let, mobility, and spend data close the tourism data gap by revealing where visitors stay, how they behave, and the real economic value they generate — in a single, defensible evidence base.
This is the shift from tourism reporting to tourism intelligence.