Foot Traffic Analytics

Foot traffic provides visitation data of mobile users to H3-9 locations, which are in the area resolution of 0.105 square kilometers. This data is used for a variety of use-cases, such as site selection, trade area analysis, investment research, and more. In this data, a mobile user will be counted once per day. Meaning, even if the mobile user left the premises and came back, their visitation to the area will be counted once. Most recent data available is for 7 days previous to the current date, and if a date is not selected for the signals providing information on specific dates, the service will only return the latest trends features. The data contain normalized US data and Global raw data.
Data Sample
Foot traffic analytics data sample
Data Dictionary
Foot traffic analytics signals (14)

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curl --request POST 
     --url 'https://api.explorium.ai/api/v1/enrich/foot-traffic-analytics' \
     --header 'API_KEY: <YOUR_API_KEY>' \
     --header 'Content-Type: application/json' \
     --data-raw $'
[{
  "Datetime": "01-01-2022",
  "Latitude": "43.06",
  "Longitude": "-88.1"
}]'

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More about Foot Traffic Analytics

What is foot traffic data?

Foot traffic data, sometimes called footfall data, is the number of consumers passing through and visiting specified areas such as retailers (retail stores) or shopping malls. The data indicates the number of people in the area during specified times, frequency of store visits, and the duration of stay. It provides traffic counts and traffic patterns such as the most popular times of the day (and days of the week) for consumer visits.

Where does the data come from?

Using laser beam interruptions is a common tool to deliver the count of consumers entering and leaving stores. Thermal imaging sensors provide another method for obtaining basic data of the number of people in a specific area. Both the tools are simple, and the data they provide may not be accurate or complete. More reliable tools for collecting data for foot traffic analysis are WiFi, Bluetooth, and GPS. At the micro-level of individual stores or shopping malls, WiFi and Bluetooth work the best. At the macro levels of large shopping areas, GPS location detection is more reliable if it gets updated in real time. GPS data provides information over a large area and cannot determine reliable information at a micro-level.

What types of attributes should I expect?

This type of data should have a minimum of two attributes: timestamped hours of operation and total hours of operation. More detailed data includes the following information about the Point of Interest (POI):
  • Number of visitors in a POI over a certain amount of time
  • Mobile devices located at a POI
  • Accurate location of the POI
  • Demographic data about the POI

How should I test the quality of foot traffic data?

Testing the quality of the data involves testing the accuracy of the POI location data and the credibility of the sources. Foot traffic databases and datasets typically get updated regularly. Nonetheless, it is a good idea to get the timeliness of data verified. To test the quality of the data:
  • Validate the source credibility
  • Verify that the databases are updated regularly
  • Ensure that the data is accurate and complete
  • Ensure that the vendor can manage the volume of data and deliver consistency at scale

Who uses foot traffic data?

Retailers use the data to optimize the store design and organize the working hours and staffing to manage the traffic. They also use the metrics to plan maintenance activities or staff breaks when the foot traffic is lower. Comparing foot traffic data with actual sales can help to calculate the sales conversion rate. The insight into the sales conversion rate helps define the store performance and compare the top-performing stores with the underperforming ones. You can use this comparison to strategize boosting the sales in underperforming stores with additional advertising or promotions. This insight also drives the decision on store locations.

What are the common challenges when buying foot traffic data?

This type of data data drives marketing strategy and plays a significant role in deciding next steps of marketing efforts and promotional activities. The accuracy of the data is critical. A major challenge for foot traffic data is the completeness and recency of the data points. The challenges are outlined in detail below:
  • Data completeness and timeliness: Foot traffic data collected from various sources may not present the complete picture that you need for accurate analysis. For example, this data must provide the most recent visitor numbers at the specified time of the day to derive any meaningful actionable insights. Ensuring foot traffic data completeness and timeliness is always a significant challenge.
  • Data accuracy: Foot traffic data drives decisions on marketing strategy and sales campaigns. Inaccurate data can result in insights that do not match the real-world situation. Verifying data accuracy can be challenging. It is important to continuously engage with the vendor to assess the data quality.
  • Source credibility: The credibility of the foot traffic data provided by various sources depends on how the vendors collect the data and ensure its quality.
  • Privacy compliance: Foot Traffic data may include personally identifiable information (PII), in which case, it must comply with the relevant region-specific privacy regulations.

What are the most common use cases of foot traffic data?

The most common use case for foot traffic data is in marketing campaign strategy. This data provides actionable insights on the number of visitors, which helps determine if the sales conversion rate meets the predicted rate. It also helps optimize resources in each store, hire temporary staff, schedule maintenance, or utilize low foot traffic periods for staff breaks. Several diverse industries use foot traffic data to power foot traffic analytics, meeting challenges unique to their target consumers. You can use foot traffic data to enrich other types of consumer demographic data for other marketing use cases in retail and financial services.
  • Marketing campaign strategy: Companies decide on a marketing campaign strategy to achieve their sales and revenue objectives. A good marketing strategy also includes processes for creating awareness of new products and gathering feedback from consumers. Foot traffic data provides information on consumer responses to advertising campaigns, which helps steer marketing efforts in the right direction. Foot traffic data combined with demographic data of store locations deliver insights into which population responds better to which promotional campaigns.
  • Foot traffic analytics: Foot traffic analysis generates valuable insights into some of the commonly asked questions in various industries such as: How many people visit the store or walk near the place of business? How long is each visit? How frequently do they visit? How do they respond to promotional activities? How do they respond to advertisements near the store? What are the most popular times and days for visits?
These insights help understand consumer preferences, optimize stores, strategize promotional campaigns, and strengthen marketing efforts.

Which industries commonly use foot traffic data?

Marketers leverage foot traffic data to help them build the marketing strategy and improve store performance. Industries that supply goods or services through retail stores include automotive, apparel, hospitality, QSR, CPG, pharmaceutical products, real estate, travel, entertainment, and telecom service providers among others. Banks, insurance providers, and financial services companies can also use this data to optimize their branch offices.

How can you judge the quality of your vendors for foot traffic data?

The quality of vendors providing foot traffic data is based on their ability to deliver a large volume of trusted data at scale. Some of the methods used for judging the vendor quality include customer testimonials and demos.
  • Customer reviews and testimonials: Customer reviews indicate how customers engage with the vendor and how satisfied they are with the services. Most of the vendor websites provide customer reviews and testimonials. They can also include case studies demonstrating the ability of vendors to rise to the challenges.
  • Demo: Getting a demo from the data provider, if possible, is a good opportunity to assess the data quality and determine if the data meets your requirements.
  • Interacting with vendor reps: Discussing your specific requirements with vendor reps is a good idea. It also gives you an opportunity to gauge the vendor's commitment to your project. Resolving your queries about data accuracy, timeliness, and the credibility of vendor sources at an early stage optimizes your process of vendor selection.