FAQs
Welcome to the Place Informatics FAQ hub.
This is where we break down the essentials, clear up common queries, and help you get the most value from our footfall, spend and location insight services.
Whether you’re exploring how our data works, looking for support, or simply curious about what we do, you’llfind straightforward answers right here.
If you don’t spot what you’re looking for, our team is always ready to help — this page is just the beginning.
Collection & Methodology
Our trusted data partners gather anonymised, permission-based GPS data from a network of app publishers. These signals come from mobile devices with appropriate permissions, allowing us to understand movement patterns without identifying individuals.
We collect aggregated GPS coordinates, timestamps, and device movement patterns. No personal information, names, or contact details are ever collected.
Accuracy varies depending on the device and environment, but most signals fall within a few metres of their real location. We apply filtering and validation techniques to ensure only high-quality data is used in our insights.
We use multiple validation layers, including signal consistency checks, noise reduction, and cross-referencing with known geographic boundaries and behavioural patterns.
Understanding the Insights
Footfall analysis measures how many people visit a location over time. It helps you understand demand, peak periods, and visitor trends.
Dwell time shows how long visitors stay in a specific area. It’s useful for understanding engagement, congestion, and the effectiveness of spaces or attractions.
A catchment area reveals where your visitors travel from. It helps you understand your audience, plan services, and target marketing more effectively.
Yes. We offer anonymised demographic indicators such as age bands, gender distribution, and lifestyle segments, depending on data availability.
Privacy
Yes. All location data is fully anonymised and aggregated. It cannot be traced back to any individual person or location.
We work only with partners who follow strict data-protection standards and comply with GDPR and other relevant regulations. All data is processed in a way that protects individual privacy at every stage.
No. The data is aggregated at a high level, meaning it shows patterns — not people.
Collection & Methodology
Location spend data shows how much people spend in and around your location, broken down by categories like retail, food & drink, and leisure. It helps you understand economic impact and visitor value.
Spend data is sourced from anonymised, aggregated credit and debit card transactions provided by trusted partners. It reflects real consumer spending behaviour without revealing individual identities.
The total transaction value is available. We never see individual transaction details, card numbers, or personal identifiers.
Spend data is updated monthly, giving you a reliable view of spending trends over time without compromising privacy.
Understanding the Insights
Spend data helps you understand:
- How much visitors spend in your area
- Which categories perform best (e.g. retail, cafés, attractions)
- How spending changes over time
- What is being spent by origin postcode
- The impact of new store openings, events and weather
Yes. When combined with location analytics, spend data can show differences between local residents, day visitors, and tourists — always in an aggregated, privacy-safe way.
Absolutely. You can explore categories such as:
- Retail
- Food & drink
- Leisure & entertainment
- Accommodation
- Services
Privacy
Yes. All spend data is fully anonymised and aggregated. It cannot be traced back to any individual person or transaction.
We work only with partners who follow strict data-protection standards and comply with GDPR and other relevant regulations. All data is processed in a way that protects individual privacy at every stage.
No. The data is aggregated at a high level, meaning it shows patterns — not people.
Collection & Methodology
Data is sourced from:
- Publicly available listings
- Partner platforms
- Automated web-scraping
- Machine-learning models that estimate occupancy and revenue
This creates a comprehensive view of the STR market across your destination.
Datasets use modelling based on observed availability, booking patterns, pricing trends, and platform behaviour. While estimates are not perfect, they provide a reliable, evidence-based picture of market performance.
Understanding the Insights
STR data provides insights into properties listed on platforms like Airbnb, Vrbo, Booking.com, and others. It includes information on availability, occupancy, pricing, property types, and host activity — always aggregated and anonymised.
Short-term rentals represent a major share of visitor accommodation. Understanding their scale, performance, and distribution helps DMOs:
- Monitor supply and demand and benchmark against other DMOs
- Track visitor behaviour
- Support sustainable tourism planning
- Evaluate economic impact
STR data typically covers:
- Entire homes
- Private rooms
- Shared rooms
- Unique stays (cabins, boats, yurts, etc.)
Common metrics include:
- Occupancy rate
- Average daily rate (ADR)
- Revenue per available rental (RevPAR)
- Booking lead time
- Length of stay
- Seasonality patterns
- Market supply and active listings
STR data does not reveal visitor origin, but GPS location data does help DMOs understand where visitors originate from.
Absolutely. Length-of-stay insights help DMOs understand trip patterns, seasonal behaviours, and the impact of events or campaigns.
Privacy
No. All data is aggregated and anonymised. Individual hosts, guests, and property addresses are never identifiable.