Footfall Data – what is it, and why is it important?

Footfall data, also known as mobility data or foot traffic data, shows how people engage with Points of Interest (POIs) in the real world. 

Retailers can understand where to open their next franchise by using data gathered from mobile devices, in-store hardware, and WiFi networks to make educated decisions. Footfall data has evolved into the most reliable indicator for the retail sector at a time when margins are contracting. The need for effective working procedures is more significant than ever.

footfall data

Real estate, retail, and investment executives base many of their critical decisions on foot traffic. Data is frequently integrated with other data, such as demographics, better to understand the specifics of a location's audience. It is also widely used to track visits to a site and discover where visitors are coming from (trade area).

The image below shows how foot traffic data was used to aid the redesign of Trafalgar Square in London by understanding movements. 

Foot traffic analytics are used in various use cases, including location-based marketing campaigns, real estate investments and leasing, and the choice of retail locations.

Questions that footfall data can answer

Retailers largely want data-based proof to guide their operational decisions. Foot traffic analytics companies like Unacast can give businesses a holistic picture of customer movement by interpreting mobility data. 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.

Where does footfall data come from?

Various sources, including in-store sensors, hardware, and geolocation hits from mobile devices, provide the raw data on foot traffic. To provide their clients with more in-depth insights, foot traffic analytics firms might concentrate on just one of these data sources or, in some cases, combine several.

footfall analytics

Mobile device geolocation data is the most typical data source. Companies are given raw location data, which is processed to assign the information to a POI. Terabytes of data are transformed into simple, understandable representations that businesses may employ using sophisticated data science approaches.

This data is more accurate and dependable when in larger locations since it can be acquired in real-time at the macro level using GPS rather than WiFi and Bluetooth at the micro level.

Top use cases for footfall data

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
  • Understand 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. 

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