Foot Traffic: The Definitive Guide
Understand everything about foot traffic – what it entails, how to measure it, and how harnessing foot traffic can elevate your business outcomes.
Understand everything about foot traffic – what it entails, how to measure it, and how harnessing foot traffic can elevate your business outcomes.
Foot traffic refers to the movement of people within and across locations. In the business ecosystem, foot traffic—often termed as “footfall”—serves as a crucial metric measuring the count of individuals visiting a distinct venue or site within a particular time frame. Foot traffic data further illuminates the behavioral trends and distinctive features of visitors in different locations.
Foot traffic describes the movement of people from place to place, and it helps businesses understand visits to a location or area of interest.
Professionals across industries utilize foot traffic to understand human behavior and mobility in the real world:
Retailers use foot traffic to evaluate store performance, conduct trade area and site analysis, and manage operations.
Commercial real estate professionals rely on foot traffic data to discover ideal tenants for commercial properties, make sound investment decisions, and understand the value of existing properties.
Municipalities and BIDs (Business Improvement Districts) study foot traffic trends to identify local service gaps, stimulate economic growth, and guide policy-making.
Advertisers leverage foot traffic data to create highly targeted promotions and assess campaign performance.
Consumer packaged goods companies utilize foot traffic analysis to optimize product placement, fine-tune marketing efforts, and manage logistics.
In the past, understanding foot traffic and visitor behaviors relied on outdated methods like manual counting, motion sensors, focus groups, and customer interviews. Now, most businesses rely on location data from smart devices. With advancements in AI and machine learning, businesses can even more effectively analyze foot traffic trends to gain valuable insights. Platforms like Unacast Insights and aggregated datasets like Unacast Location Analytics offer highly accurate and customizable foot traffic analytics powered by machine learning. This modeled data not only provides visitor counts but also reveals details about visitor origins and subsequent movements, all while safeguarding individual privacy.
The foot traffic and location intelligence ecosystem is generally built on the supply of quality location data. Yet location data also has a natural confluence with many other forms of big data. When one is used to augment the other, the resulting stream is a flow of real world insights that can predict revenue, detect change sooner, and measure performance.
Unlike typical data products that rely solely on GPS device-level supply, Unacast uses a machine learning model that is more robust and less dependent on data supply fluctuations due to its multitude of data sources.
The process begins with pseudonymized first-party location data. That data is then combined with contextual data including demographics, industry trends, venue attributes, historical data, and more. We trained our machine learning model to learn the relationship between different data sources and our historical mobility insights, with our model comprising more than 120 features.
This machine-learning powered data allows us to create curated datasets that make it easy to work with location analytics. When validated against ground truth data, Unacast’s models recorded an R-squared value of up to .92, widely considered to be best-in-class.
Foot traffic has the power to dramatically improve strategic decision making, customer targeting, and business operations. It can unlock enormous insights into customer behavior, location successes (or failures), and competitive opportunities.
Foot traffic is beneficial for:
Foot traffic can provide insight into store performance, neighborhood changes, and so much more.
Within about two months of the start of COVID, we didn't need to rely on anecdotal evidence of urban exodus anymore — it was in the data. Whole urban centers went dark, while smaller areas lit up with an increase in activity.
This created new foot traffic patterns in growing communities with evolving needs for public services and spaces. This human reshuffling also meant retailers and restaurateurs were flush with options for new store locations, reshuffling site selection processes for many real estate investment teams.
With foot traffic, businesses can identify changes faster and also predict future business performance. Learn more in our report, “Does Foot Traffic Predict Business Performance?”
Foot traffic can help real estate investment teams make the best decisions in where to invest. This is because:
Leading home builders use foot traffic to identify income trends across regions, and select areas with prime growth opportunities.
We believe we've set ourselves up for success to weather the pending storm regardless of its status as a recession or correction. We feel confident knowing we have the location data we need.
Market Intelligence Director, National Home Building Company
Foot traffic insights can be used by advertising and marketing professionals to reach their target audience and personalize their messaging. Advertisers can use foot traffic data to track the movement of potential customers and target them with relevant ads or offers. Additionally, foot traffic can be used to track the effectiveness of ad campaigns and optimize them for better results.
Just like you can use foot traffic analytics to understand your own business, you can also use it to get insight into your competition. This is of particular importance for retailers, restaurants, grocers, coffee shops, and big box stores.
You can understand what types of visitors are going to your competitors, and how long they spend at their stores. You can dig into where else your competitors’ customers are going, and what other brands they visit, to find ways to complement your own offerings. You can also see the home and work locations of your competitors’ visitors, meaning you might be able to target them with a specific promotion or a new store placement in their area.
Retailers use foot traffic trends to improve customer experience and brick-and-mortar performance. Retailers use foot traffic data to track customer movements in their stores, identify popular products, and optimize store locations and layouts. They use it to stay ahead of their competition, and to personalize marketing and promotional offers to customers based on their locations.
Retailers also use foot traffic as a leading indicator for revenue, and to select the best new site for a retail location. A retailer using foot traffic might pinpoint an area that is drawing foot traffic from its target customer profile, and jump on that location before its competitors.
"Location data is more important than ever because it takes data integration to the next level to account for evolving shopping habits and provide retailers the insights to adjust accordingly."
VP Global Solutions, sensor company
More and more companies and software platforms are looking to use foot traffic data in their own solutions. From insurance companies to adtech platforms, there are endless creative applications across industries. Foot traffic is becoming a must-have for businesses to make informed decisions and optimize their processes.
In one example, a Fortune 500 insurance company used a set of foot traffic metrics to tie a throughline between identified risk and the number of claims submitted. They were able to confirm which times, days, and seasons were most likely to result in increased claims, and to understand the impact of major events.
While location data is one piece of the puzzle, we believe that it paints a holistic picture helping us generate more accurate quotes.
Chief Underwriting Officer, Property and Casualty Insurer
A group of boutique hotels in tourist hotspots employs foot traffic analysis to adjust their pricing strategy dynamically. By monitoring foot traffic trends in their vicinity and correlating them with local events, seasonal visitor patterns, and competitor occupancy rates, the hotels can forecast demand peaks and troughs more accurately. This insight allows them to offer competitive rates during off-peak times to attract more guests and optimize pricing during high-demand periods to maximize revenue.
A consumer goods company planning to launch a new beverage uses foot traffic data to identify the most viable locations and timings for promotional events. By understanding where and when potential customers are most likely to be, based on historical foot traffic patterns and demographic insights, the company can deploy mobile pop-up tasting stands in high traffic areas during peak times. Simultaneously, they target localized digital ads to mobile devices in the area, significantly increasing product awareness and trial rates among the target demographic.
A major transportation organization uses location data to improve efficiency and reduce costs. It uses foot traffic insights to optimize routes, reduce fuel consumption, and improve safety. Location data can also be used to track and manage assets, such as vehicles and cargo.
Foot traffic data can be used by governments, law enforcement agencies, and private companies to improve safety and security. For example, foot traffic can be used to track the movements of individuals and detect patterns that may indicate criminal activity. Additionally, location data can be used to monitor critical infrastructure and detect potential security threats.
Some ways to work with foot traffic include:
The easiest way to get started with foot traffic is through a location insights platform like Unacast Insights. The platform provides foot traffic data, trends, and automated AI summaries that greatly simplify the work of data analysis. It’s location intelligence made easy.
Foot traffic analytics is the next-most sophisticated level at which you can work with foot traffic. Our machine-learning powered location analytics solution provides aggregated, clean datasets that help you understand foot traffic to points of interest or venues that you choose. With more than 120 features, our machine learning models provide the most comprehensive foot traffic insights without being dependent on location data supply. When validated against ground truth data, Unacast’s models recorded an R-squared value of up to .93, widely considered to be best-in-class.
Device-level location data is the ultimate solution for large or complex enterprises needing high-quality data across the globe. With this option, customers get licensed data access, scoped and delivered to their exact specifications, and forensic flagging that lets you choose only the signals that meet your accuracy criteria.
There are a number of options to connect foot traffic data to geospatial tools, including solutions for data processing, data analysis, and data visualization. ArcGIS Pro from Esri is a powerful GIS software that lets you explore, visualize, and analyze data, create 2D maps and 3D scenes, and share your work online.
Another powerful geospatial solution is CARTO, a spatial analytics platform used to optimize and predict future outcomes through the power of geospatial data science.
For telcos and other first-party location data owners, there is a massive opportunity to turn raw data into foot traffic insights.
The Unacast location data processing engine is used by telcos and other first-party data owners to process their data into valuable, privacy-friendly, human mobility insights, at scale — without the data ever leaving their domain. This key difference means you can transform your data into insights without ever having to worry about data privacy. Deploy our platform in your data clean room or cloud to ensure data never leaves your secure environment.
Find out why best in class companies partner with Unacast for their location data needs.
Given the high stakes of decisions relying on foot traffic data, it is vital to opt for a location intelligence solution that guarantees accuracy, precision, and coverage — and one that prioritizes stringent privacy compliance.
Unacast’s location intelligence solutions tick all these essential boxes, equipping professionals across industries with the necessary tools to analyze foot traffic for any location or broader geographical area. Unacast leverages advanced data science techniques and machine learning to extrapolate foot traffic insights from location data. With solutions for every phase of the data analytics journey, Unacast allows you to easily analyze visitation patterns to chains, stores, and other points of interest (POIs) nationwide, in addition to custom locations, neighborhoods, zips, and so on. Unacast also offers a diverse range of psychographic and demographic datasets that customers can seamlessly integrate into their analyses.
Foot traffic is the foundation of an excellent location analytics process. It’s a critical metric for deciphering human behavior and real-world movements. By analyzing foot traffic trends, retailers, urban planners, CRE brokers, and others can mine valuable insights into consumer behavior, make informed decisions, and improve performance. As location intelligence capabilities continue to evolve and become increasingly sophisticated, businesses across industries will find accurate and current foot traffic data indispensable.
Foot traffic refers to the number of people who visit a location in a particular period of time. For example, foot traffic to a shoe store indicates the count of people who visit the store, regardless of whether they buy something or not. Foot traffic can be used to show visit trends, peak times, length of visits, and so much more.
By definition, foot traffic refers to the number of people visiting and moving around a location (e.g., supermarket, restaurant, retail store, etc.). Foot traffic also includes pedestrian activity. Businesses may also use the term “footfall” to describe foot traffic.
An example of foot traffic is pedestrian activity, i.e., the number of people walking on a specific street. We use the term when talking about how many visitors a business gets, or how many people travel through an area. It considers how many pedestrians there are in the area where a shop is, including those who don't walk in.
Traditionally, locations might use a physical counting device, such as a clicker counter. This is an outdated method that can help businesses manually track visitors. The most scalable way to measure foot traffic is through location data collected from smartphones and other devices.
