What is mobility data and location data, and why does it matter? 

Key takeaways

Introduction

Retail brands, QSR chains, and other location-dependent businesses operate at the intersection of digital marketing and physical visits. While e‑commerce continues to grow, most revenue is still generated by real‑world visits — to stores, restaurants, curbside lanes, and drive‑thrus.  

For businesses that depend on in-person visits, understanding how people move through the real world is essential. That understanding comes from different forms of consumer intelligence – most commonly location data and mobility data, which capture different signals about behavior. 

Location data is foundational to modern marketing — and for good reason. It informs how we target, how we measure, and how we prove performance at scale. But even the best location data has limits. 

When location signals are accurate and responsibly sourced, they tell us where — a visit, a stop, a moment in time. That’s genuinely useful. It anchors measurement and connects media to outcomes. 

What it doesn’t reliably tell us is how people got there or what shaped the decision to show up at all. 

Movement is the missing layer. The paths people take, the patterns between moments, the behavioral context that turns a data point into an insight worth acting on. Without it, we’re working from a partial view, one that can support reporting but may not be enough to drive confident decisions. 

That’s the gap mobility data fills. 

The fullest view comes from combining location data and mobility data. Mobility data captures aggregated and anonymized driving patterns — connecting typical routes and timing into a comprehensive view of real‑world movement. Whereas location data reveals visitors, timing, and dwell time, mobility data uncovers meaningful context. It reveals how these visits fit into consumers’ everyday routines, helping you understand where your brand can more seamlessly fit into their lives. 

Why consumer intelligence matters for visit‑based businesses 

Any business built around physical locations depends on understanding how people move through the real world. Although sales data can tell you what happened at the register, location data reveals how many people visited your store whether they made a purchase – and how long they stayed there. With this consumer intelligence, a business such as a retail chain can understand their foot traffic conversion rate, or their ratio of purchasing customers to total visitors. With that insight, businesses can estimate how many visits it takes to sustain or grow profitability. 

Location data and mobility data: A quick overview 

Location data and mobility data are often talked about together, but they are not the same thing. Each captures different signals. Each has strengths and limitations. And neither tells the full story on its own. 

 At a high level: 

• Location data helps answer, “Did someone visit, and how long were they there?” 

• Mobility data helps answer, “How did they get there, where else did they go, and how does this visit fit into their day?” 

Combining both creates a clearer, more reliable picture of real‑world behavior. 

What is location data? 

Location data is information about where a person or object (such as a car or mobile device) is at a specific moment in time. This data may be collected through GPS, WiFi, or even physical data capture devices such as on-site sensors.  

For businesses looking to derive customer insights, location data isn’t sufficient on its own. The most effective data strategies combine multiple datasets to create a more complete and reliable view of customer behavior. A full toolkit of data – including mobility data – enables more strategic decision‑making. This range of data helps businesses understand not just whether customers visited, but how and why they did. 

What are cell phone tower pings? 

Cell phone tower pings are a byproduct of how mobile networks route calls, texts, and data. They’re intermittent and imprecise — typically too coarse for store-level decisions.  

The primary users are public agencies — transportation, public health, emergency management — applying this data to track large-scale population movement. 

How often are cell phone tower pings collected?

Cell phone tower‑based location data is not collected continuously. Signals may range from a few records per day to many within a short time window, depending on user activity, movement between coverage areas, and routine network management. As a result, this data establishes basic — not granular — location intelligence. 

What is foot traffic data, also known as footfall data? 

Foot traffic data — also called footfall data — measures visits to a physical location: when people arrive, how long they stay, and how patterns shift over time. Unlike a single location ping, foot traffic data reflects aggregated observations over time.  

Retailers and QSRs use it to assess store performance, evaluate marketing impact, and understand cross-shopping behavior. Public sector applications include city planning, tourism analysis, and district-level insights.  

How is foot traffic data collected? 

Foot traffic data can be captured in several ways: 

• Continuously through physical sensors such as break beams or thermal counters 

• Intermittently through mobile device signals from users who have opted in to share their location data 

• Modeled from sampled movement data to estimate total visitation* 

*Modeled mobile footfall does not observe every individual shopper. Instead, it uses samples and statistical modeling to estimate overall visit volume and trends. 

How often is foot traffic data collected? 

Foot traffic data gathered via mobile devices is collected intermittently. Location updates occur more frequently when a person is moving, but timing varies based on app behavior, device type, and operating system battery management. As a result, foot traffic data is typically reported in time buckets such as hourly, daily, or weekly intervals. 

What is mobility data? 

Unlike location data, which identifies a place at a specific point in time, mobility data captures movement over time. Mobility data is more granular and behavior-rich than location data. While the term can broadly include many modes of transportation, in this context mobility data refers specifically to driving behavior. 

Mobility data captures how, when, and where people drive — connecting routes, timing, and repeat patterns into a coherent picture of real‑world movement. This level of detail reveals not just where visits occur, but how they fit into customers’ daily routines.  

How is mobility data collected? 

Mobility data is collected from mobile apps or directly from in‑vehicle sensors of users who have opted in to share their location data. On smartphones, data collection begins when movement patterns indicate driving and ends when that movement stops. With in‑vehicle sensors, data collection starts when the car is turned on and stops when it’s turned off. All of this data is aggregated and anonymized. 

 How often is mobility data collected? 

Mobility data is typically collected every few seconds while a vehicle is in motion. Frequency may vary by device type or vehicle manufacturer. 

What are customer journeys, and what are routes? 

A journey is the full travel path a customer takes throughout their day. It includes multiple routes. For example, many families’ journeys on a Saturday may take three hours or so and include multiple roughly half-hour or hourlong routes from home to the grocery store, from the grocery store to a big box store, from the store to a fast casual restaurant, and then from the restaurant back to their home. 

Why does data frequency matter? 

The goal of any consumer intelligence strategy is to understand customer behavior well enough to act on it. Data collected every 20-40 minutes can establish general patterns, but high‑frequency data fills in critical gaps — especially for businesses that depend on speed, timing, and short visits. 

High‑frequency mobility data makes it possible to capture: 

• Short visits alongside longer visits 

• Complete journeys as well as individual routes 

• Visits to other POIs such as competitor locations 

When combined, location data and mobility data create a clearer and more reliable picture of real‑world behavior — revealing opportunities to improve operations, marketing, and customer experience.  

Better business insights start with more complete data coverage 

Businesses built on visitation models must answer fundamental questions: who visited, when they arrived, how long they stayed, and where they went next. 

But location data alone is limited; it’s a snapshot, not a movie. Understanding behavior requires seeing movement over time. This is where mobility data enters, not as a replacement for location data but as a missing layer. 

The most accurate answers to these fundamental questions emerge when organizations combine multiple forms of consumer intelligence. 

Together, these datasets provide the most complete view of customer journeys — without over‑relying on any one signal. 

The takeaway for businesses 

There is no one-size-fits-all dataset. Each type of data has strengths and limitations, and the right approach depends on the business problem being solved. 

When the goal is to determine customer volume at a specific time and place, location data will suffice. But when the goal is to understand the full customer journey, mobility data is essential. Mobility data delivers the most complete view of consumer movement, enabling better decisions across operations, marketing, and customer experience. 

Mobility data helps you understand how your customers move through the world so that you can meet them where they are.