Footfall data, also known as foot traffic or mobility data, is an increasingly powerful source of information for leaders in retail, real estate, investing, and marketing. Understanding the patterns behind how, where, and when people move is critical for decision makers across sectors.
Equipped with reliable footfall analytics, real estate and investment executives can glean predictive insights for finding successful investment opportunities. Marketers can plan and execute location-based marketing campaigns to reach highly targeted audiences. Retailers can better understand where to open their next franchise by using data gathered from mobile devices, in-store hardware, and WiFi networks to make educated decisions. In fact, footfall data has evolved into the most reliable indicator for the retail sector at a time when margins are contracting.
The image below shows how foot traffic data was used to aid the redesign of Trafalgar Square in London by understanding movements.
What is footfall data?
Footfall data, also referred to as mobility data or foot traffic data, shows how people engage with Points of Interest (POIs) in the real world.
Footfall data is sometimes called “people counting,” and although tracking the total number of people in a given space is a critical part of footfall data, that’s only the surface. What makes this data so valuable to business leaders is that it’s a holistic way of tracking patterns of behavior based on location, time, demographics, and other metrics.
Often footfall data is integrated with other sources of data, such as demographics or market trends, for more robust insights. It is also widely used to track visits to a site and discover where visitors are coming from (trade area). Footfall analytics have become a powerful force in marketing campaigns, real estate investing, and retail operations.
Where does footfall data come from?
Various sources, including in-store sensors and geolocation hits from mobile devices, provide the raw data on foot traffic. To provide their clients with more targeted insights, foot traffic analytics firms might concentrate on just one of these data sources or, in some cases, combine several sources for broader, deeper insights.
Mobile device GPS data: The most common data source is geolocation data gathered from smartphone and mobile apps. Mobile GPS data is collected in real-time at the macro level and is typically provided as raw location data which can then be processed and assigned to a specific POI.
WiFi and Bluetooth data: WiFi and Bluetooth data may also be used in footfall data collection, although this relies on the in-store connection and provides micro level data as opposed to the macro level data gathered from GPS. Typically, in larger, more populated areas, GPS location data is preferred.
In-store sensors and hardware: Sensors and video camera systems installed on the exterior or interior of a location can collect on-the-ground foot traffic data, and this technology has improved significantly in both cost and accuracy in the past several years.
External sources and trends: For a more powerful dataset, external sources like weather, regional demographics, and industry trends can be integrated with people counting data to provide more accurate, meaningful information.
From these sources, terabytes of data are transformed into simple, understandable representations that businesses may employ using sophisticated data science approaches.
Questions that footfall data can answer
Retailers and investors want data-based proof to guide their operational decisions. But raw data alone is not actionable. Foot traffic analytics companies like Unacast can give businesses a holistic picture of customer movement by interpreting mobility data—making it meaningful for decision-makers. The data that is most helpful to retailers tends to be:
- The number of consumers visiting your business
- The percentage of people in the area that visit your business, known as the capture rate
- The patterns for when people visit your business (hourly, daily, weekly, monthly)
- The amount of time people spend visiting your business
- Do people come back and stay loyal to your business?
- The demographics of consumers such as age, gender, income group and education level
Retailers in the real world benefit significantly from foot traffic data since it gives them a comprehensive understanding of consumers and ultimately teaches them how to get more customers into their stores. Analytics solutions give users the same degree of insight as their online equivalents, giving them the information they need to increase productivity.
Top Use Cases for Footfall Data by Industry
Foot traffic data can have a considerable impact on various industries. Below are some of the top use cases.
Supply Chain and Logistics
Footfall data helps to measure consumer activity at different locations to optimize supply chain planning. It can help businesses understand the changing demographics across areas and how they might impact performance. Site analysis and venue-specific site traffic data support decision-making for opening and closing sites through a better understanding of their potential.
Data can show how much stock is required at particular places and why. Retailers can gain a broad understanding of their stock needs from information on shop visits. Still, a more detailed analysis can be done using the information on the demographics of trade area visitors and the places they frequently visit before and after the POI. Retailers can ensure the appropriate stock is going to the correct location by combining it with proprietary sales and target customer data.
You can read here about how gas prices can affect foot traffic near pumps.
Retail
Retail stores perhaps have the most to gain from footfall data.
During the busiest shopping hours, you may ensure more employees are working on the sales floor. Likewise, refrain from overstaffing during busy times. By doing this, superfluous operating expenditures will be avoided.
Heat-mapping features of foot traffic software can help you plan merchandise placement across the store. High-traffic areas can stock the best-selling items.
If you are aware of your retail store's busiest times of day or hours, you may schedule flash sales or other special promotions for specific times. Doing this may potentially contact more consumers and sell more goods.
Retailers can also see how seasonality, road traffic and local events impact the foot traffic near their stores.
Unacast has several retail case studies that cover site selection, competitor analysis, performance and forecasting.
Real Estate
Footfall data can help the real estate industry gain insight into the best investment opportunities within a specific area. The raw data comprises mobility information through GPS, visitor trends, and market analysis. Businesses and investors can understand the customer profile within particular regions, and which areas are most highly trafficked. Unacast also provides migration patterns data to help real estate developers identify hot new areas.
Financial Services
Financial services use cases may not seem as evident as retail or real estate. However, financial firms can use footfall data to model consumer behavior, conduct trade analysis for investment opportunities, manage portfolios and benchmark the competition. Property level insights could help underwriters build more specific risk assessments.
Read the Unacast case study on how a Fortune 500 insurer optimized for profitability using location data. The initial results show improved loss ratios, which are critical to success.
Insurance
Insurance companies use foot traffic data to take the guesswork out of assessing risk and pricing policies. Unacast helps insurance providers to translate real-world behavior into valuable insights. Examples of where footfall data can help insurers include:
- Protecting against loss due to lockdowns, geohazards or evacuations
- Understanding the relationship between risk and consumer behavior, enabling pricing optimization
- Analyzing the impact of hybrid working schedules on risk
- Understanding the potential for natural disasters using footfall data
Objective foot traffic data enables the insurer to evaluate and write commercial risks properly. It provides the solid proof insurers need for accurate quotes outside of traditional claims history or revenue-based underwriting.
Software and Analytics
Location data for software and analytics helps businesses to enhance existing datasets and build better products. Companies use location data to forecast, segment, and measure performance to decide what comes next for their organization.
Foot traffic data can improve predictive models and enrich existing data, such as customer profiles. It also helps enhance segmentation by targeting the right person at the right time. Real-time data means you can forecast with confidence and identify precise areas for growth.
Top 5 Footfall Traffic Data Providers
As footfall traffic data becomes an increasingly important type of intelligence for operational decision making, the number of data providers on the market has grown tremendously. That means more providers and platforms to choose from—but it also means more factors to consider in finding the provider that’s right for your organization.
All quality intelligence providers should collect data from reliable sources with sound, ethical methodology. Beyond data quality, however, there are some additional key considerations for finding a footfall data provider that will meet the needs of your organization.
Integration: is the data raw or ready to be integrated into your existing software and systems?
Analysis and visualization: in addition to datasets, are they providing tools for analyzing and visualizing that data into meaningful insights?
Coverage: do they provide data from the regions you need—US only, North America, global?
Here we consider five leading footfall intelligence providers, including our Unacast platform, and what they offer.
Unacast
With a focus on privacy-maintaining foot traffic datasets and migration patterns, we leverage multiple sources, including device GPS data, weather, demographics, industry trends, and specific property data. We clean and stabilize the data using machine learning, and provide focused, curated datasets.
Placer AI
A modern, API-driven foot traffic intelligence provider focused on location data from the United States.
Carto
Carto is one of the most popular cloud-based location intelligence companies on the market due to its intuitive interface for users with limited GIS programming experience.
Bluefox
BlueFox collects data from WiFi and on-site sensors, and they provide a modern, cloud-based solution with a robust API that allows integration with third-party systems.
Veraset
Focused on gathering, curating, and delivering high quality foot traffic data via mobile GPS data, they provide raw and pre-processed population movement datasets.
Start using footfall data today
If you’re ready to get started with footfall data analytics—or you just have more questions about how it all works—book a meeting with Unacast to get tailored recommendations for your organization. Work with a team of data scientists to get the perfect insights from one of the most accurate sources in the industry. If you are ready to level up your data game, speak to Unacast today.
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