How to Measure Foot Traffic

The amount of pedestrian traffic (AKA “foot traffic”) at a given location can have a big impact on business success. Whether you want to open a new store, run offline ads, or tailor your open hours to optimize walk-ins, knowing where people walk and when is key.

But foot traffic patterns can be difficult to measure. Many businesses are forced to rely on incomplete data sources such as consumer behavior surveys or counters that only capture in-store traffic to inform decisions that can greatly impact their bottom line. Inferring actionable takeaways from these sources can be risky due to limited geographical and temporal data coverage or responder bias that can skew results.

So how can businesses get reliable insight into real foot traffic patterns to make data-driven decisions that ultimately drive revenue? In this article, we’ll explore some of the common ways to measure foot traffic, including:

• Manual counts
• Automated people counters (e.g., on-location sensors and cameras)
• Consumer surveys
• On-demand foot traffic data platforms (like StreetLight)

You can use this guide to determine which method works best for you, whether you need basic entry counts, customer behavior insights, or multi-location coverage. We’ll also explore how advancements in foot traffic analytics are helping businesses fill key data gaps left behind by other common methods.

How to Set Up Your Foot Traffic Measurement for Accurate Data

The collection method you choose to gather foot traffic data can have a major impact on how reliable that data is for different use cases.

For example, manual counts are limited to a specific time frame and subject to human counting errors. That means you may not get data that reflects seasonal differences or off-peak hours, depending on the collection window(s) you choose.

Additionally, automated people counters like Wi-Fi sensors or thermal cameras have a limited spatial scope, typically only capturing foot traffic data based on those who enter a location or pass directly outside it. While this can be useful for tracking visitation patterns, it’s less useful in understanding the broader scope of foot traffic around a given location.

For use cases like site selection and advertising, among others, visibility into this broader scope of foot traffic is key to help decision-makers understand potential customer demand and how your customers move beyond the range of a single point of interest. Measuring store visits alone can’t provide insight into potential demand and how to capture it.

When using these methods, defining clear parameters is crucial to gathering accurate data. Oftentimes, foot traffic inaccuracies stem from unclear definitions. Take care to:

• Clearly define your place boundary (e.g., a single door, your full site, or a specific road segment)
• Select your reporting window (e.g., a specific hour, a day, or a full week. Consider how activity may change over the course of a day, week, or year when choosing your reporting window, as this can impact how representative your counts are)
• Decide how you want to treat repeat visits and pass-throughs (i.e., do you want to understand the total number of visits, or is it more important to know how many unique visitors stopped in? What about people who pass through the place boundary without stopping to browse or purchase anything?)

Additionally, be aware of common counting errors with these methods:

• Shared entrances or poorly defined place boundaries can lead to misattributed foot traffic counts (e.g., mistakenly counting a neighbor’s visitor as your own)
• Passersby can mistakenly be counted as visitors, especially when they pass closely to a door sensor or camera
• Double-counting can occur when you have multiple sensors throughout your site, or simply due to human error, in the case of manual counts

On-demand foot traffic analytics such as those offered by StreetLight can help avoid these common counting errors while offering increased spatial and temporal coverage that may not be possible with other methods. To see how StreetLight rigorously validates its foot traffic counts for every road and trail in the U.S., check out this white paper.

Foot Traffic Calculator: KPIs to Consider (With Simple Formulas)

Once foot traffic data has been collected, the next step is to use that data to derive actionable insights that drive profitable business decisions. Understanding your Key Performance Indicators (or KPIs) is key to this part of the process.

There are many KPIs you might want to consider when translating foot traffic data into performance-driving decisions. Let’s explore some of the top KPIs that inform site selection, marketing efforts, and business operations. 

Key Metrics to Consider

Total visits or total trips

Total visits is a measurement of how many times people visited a specific location within a given time period. This measurement includes visits from people who may or may not take a desired action such as making a purchase. It can also include repeat visits from the same individual.

Total visits is a useful metric in understanding overall consumer demand, measuring the success of certain marketing strategies, and optimizing operational decisions such as open hours and staffing plans.

Similarly, total trips is a measurement of how many trips were made on foot to or through a particular location. While total visits specifically looks at how many times people visited a location (i.e., stopped at or entered within the location you define), total trips may additionally include people who passed by or through your location.

Understanding total trips can be especially useful in identifying high-traffic areas that could support a new store location, expanded operating hours, or additional staffing or marketing efforts. Likewise, total trips can be a helpful metric to analyze alongside store visitation patterns, helping illuminate areas where it may be possible to increase foot traffic into a particular location based on foot traffic patterns nearby that location.

Total trips can often be further broken down into pass-through trips vs. trips that end in your location. This means total visits can often be derived from a larger total trip count. This can be useful to measuring not just actual visits but also potential visits, helping decision-makers understand how much total foot traffic could translate into visits. We discuss this further in the section on capture rate below.

Conversion rate

Conversion rate is a measure of how often foot traffic actually converts into a desired action, as defined by you. Often, that desired action is making a purchase, though conversion actions could also include other desired behaviors such as signing up for a membership program, inquiring about a promotion, picking up a brochure, or simply entering your location.

Whatever conversion action you want to measure, the formula is basically the same. Divide the total number of conversion actions taken within a given time period by the total number of visits (or trips) in that same time period. The resulting number is your conversion rate.

This metric is particularly useful in understanding the impact that marketing efforts, customer service, and other factors may have on the likelihood that visitors take a specific action (such as making a purchase) within your location.

A low conversion rate can signal that, even though people are interested, they are ultimately not persuaded to take action during their visit. Meanwhile, a high conversion rate can signal that visitors’ experiences at the location are successfully driving them to take the actions you want them to take.

Capture rate

Capture rate is similar to conversion rate, and the two terms are often used interchangeably, though there is a subtle difference. While a “conversion” can be any type of desired action defined by you, a “capture” is typically a specific type of action—namely, entering a particular location.

Capture rate can be useful in understanding how often foot traffic near your physical location translates into actual visits.

To calculate capture rate, divide the number of total visits by the number of total trips.

How to Use Foot Traffic Data in Retail Stores

Once you have your KPIs measured, how do you connect these metrics to actions? We’ve discussed above what types of decisions common KPIs can be useful for. Now let’s cover a few common scenarios faced by retailers and dive deeper on how you might use foot traffic analytics to get a competitive edge.

Scenario 1: Staffing based on peak hour analysis

To ensure you have the right number of staff working at any given time, you need to understand how customer demand ebbs and flows during the day and week. Identifying your peak hours of foot traffic is a great first step to optimizing staffing.

To perform a peak hour analysis, separate foot traffic counts for your store into hourly bins and note the hour(s) when the counts are highest. You may want to run a peak hour analysis for each day of the week, or at least analyze a typical weekday vs. weekend day to understand how optimal staffing may shift over the course of a week.

These analyses can also help you identify optimal operating hours for your store, avoiding times when traffic is especially low and prioritizing hours where traffic is especially high.

Scenario 2: Site selection based on foot traffic with customer profiles

Understanding pedestrian and vehicle traffic at a particular location is key to identifying the most advantageous site for a new store — but not every traveler is necessarily a potential customer. Pairing total counts with data on traveler demographics can help you understand where traffic is most likely to translate into store visits and sales.

Some foot traffic analytics providers, like StreetLight, can pair foot traffic counts with aggregated demographics derived from the most recent census data to help you understand not just where consumers travel, but specifically where your target customers frequent. For example, StreetLight allows you to measure the overall breakdown of traffic by household income, family size, and other factors.

Why StreetLight Is the Gold Standard for Measuring Pedestrian Mobility

 StreetLight has been a leading provider of traffic and mobility insights for over a decade, earning the trust of businesses, agencies, and firms across North America. We navigate the landscape of available data sources and rigorously validate our metrics so our customers can trust they’re getting reliable insights that power smarter decisions.

Businesses trust StreetLight to deliver the most reliable, up-to-date, and granular metrics available on the market. StreetLight helps businesses leverage foot traffic and vehicle activity metrics to:

• Identify growing (and shrinking) markets and sites for your business
• Choose the most advantageous locations for real estate investments
• Optimize store operations like open hours and staffing
• Measure the success of marketing, merchandising, and layout decisions
• And more

For example, Motionworks uses StreetLight to measure the impact of billboard advertising and understand how specific customer profiles move around a given location to help their clients make data-driven marketing decisions.

Similarly, NaviRetail leverages StreetLight’s traffic count data to help retailers evaluate potential new store locations and identify where high consumer traffic can support those real estate investments.

Additionally, unlike other foot traffic data providers, StreetLight also offers bike activity metrics at the road segment level. When businesses have visibility into multiple modes of active transportation (i.e., both walking and biking), they are able to leverage a more complete picture of how potential customers move, what they’re likely to buy, how they encounter ads, and more.

On top of biking and walking data, StreetLight also offers the most comprehensive repository of vehicle activity data in the marketplace. This demo video explores how retailers can use vehicle traffic data for site selection, operational decisions, and more.

To learn more about how businesses like yours are using StreetLight today, visit our page on traffic data analytics for business.

To see if StreetLight’s foot traffic analytics could support your business goals, reach out to a team member today.

FAQs 

1. What is considered foot traffic?  

“Foot traffic” can mean a few different things depending on the context. Sometimes, when businesses talk about foot traffic, they are referencing the number of people who walk into a particular store or other point of interest.

Additionally, foot traffic may be used more broadly to refer to the number of pedestrians who walk to or through a particular area. This can include people walking along a particular road or intersection, not just those who enter a store.

This broader definition of foot traffic can be useful for businesses who want to measure how nearby pedestrian travel may translate into store visits at a potential new retail location, or event planners and venue managers who want to understand how event-goers and other pedestrians may arrive, depart, or route around a venue during an event.

2. How is foot traffic calculated?

Foot traffic is calculated by counting the number of pedestrians that travel to or through a particular location within a particular time frame.

For example, foot traffic can be measured by calculating Annual Average Daily Pedestrian Volumes (AADPT), which sums up the total number of pedestrians traveling at a particular location each year, divided by 364 days, to arrive at a daily average number of pedestrian trips for that location.

To learn more about how StreetLight calculates and validates its foot traffic counts, see our AADPT and AADBT Methodology and Validation white paper.

3. What is the best way to track foot traffic?

There are multiple ways to track foot traffic, including sensors installed at retail entrances, exterior cameras, and manual counts. Each of these methods can be useful for measuring visits to a store or point of interest. However, they each have limitations: sensors and cameras may only capture a narrow view of foot traffic entering or passing by a location, while manual counts are often resource intensive and only capture a snapshot in time.

Foot traffic analytics derived from big data can help fill in the gaps left by these other methods. Foot traffic analytics based on location data can offer more geographic and temporal coverage, which is critical to making well-informed site selection decisions as well as event management, retail operations, and other business decisions that are impacted by customer demand.