This article is brought to you by Arity.

Retailers know their customers’ journey inside their stores. But what about before they come to the store? Where are they going after?

The answers to these questions—and more—can be found in mobility data, said Chase Davis, strategic solutions engineer at Arity. Mobility data, he continued, offers detailed insights that “uncover growth opportunities that location data simply can’t see.

“Location data [or footfall data] is good. Mobility data is better,” he said. With this data, retailers can de-risk their innovations and improve their pilot programs because it gives them a greater understanding of what their true customer base is by filling in the gaps that location data can leave.

According to Davis, there are three main challenges with location data that are solved by mobility data.

Limited predictive capability. Location data captures only snapshots, pulling data only three or four times a day, “often missing the short, fast visits that define convenience retail.” According to NACS research, the average convenience store visit is between three and four minutes—a span of time that can easily be lost with location data.

Comparatively, Arity’s mobility data is continuous, high-frequency and high volume. More than 50 million drivers are opted in, and Arity receives signals every 15 seconds. Arity did an analysis with a QSR and found that its mobility data, compared to foot traffic data, revealed more than two times the number of customers that came through the QSR—foot traffic data missed identifying those customers.

Incomplete customer journey. Traditional data struggles to capture micro-moments from customers, including visiting drive-thrus or other competitors in the area. Ultimately, Davis said, it offers an incomplete picture of the customer journey.

“Our mobility data provides a holistic, comprehensive view of a customer journey. With Arity, retailers not only gain a greater understanding of how often their customers visit their own store, but it also shows the leakage rate of customers,” he explained. “Retailers can know exactly how often their customers pass by their c-store for the competitor down the street, or the percentage of customers who stop at a QSR after visiting their store.”

Fragmented and reactive data. “The insights that come from sources like location data can often be delayed and fragmented for retailers because it’s designed to collect random pings from customers over time,” Davis said. Using traditional data only looks at what’s happened in the past, and retailers must wait to access actionable data—leading to slow innovation cycles. But, when data comes from technology that tracks—and anticipates—actual driving routes, c-stores can make proactive decisions based on real-world behavior and avoid distortions from less reliable data sources.

To learn more about how mobility data can help a retailer win customer loyalty, look for part two of this two-part series brought to you by Arity.