Location data predictive of retail store closures

inMarket loyalty report suggests which retailers will be the next ones to go.

Chat with MarTechBot

Mobile Shopping Store Visit2 Ss 1920

As marketers are discovering, mobile location data can be used for many purposes. Among them, according to inMarket, is predicting retail store closures.

The company’s SDK (software development kit) is integrated into 700 apps, and it sees more than 50 million active mobile devices in the US. One of the data sets the company captures is the frequency of retail store visits. This can be translated into a loyalty metric and benchmarked by retail segment.

For a new retail report, the company tracked non-grocery store visits between January and May and assigned each store a score based on visitation frequency: “The average loyalty score for all non-grocery retailers in Spring 2017 was 1.45.”

Top and bottom 10 retailer rankings by customer loyalty (visits)

Screen Shot 2017 06 07 At 1.58.48 PM

Those on the bottom 10 list on the right have announced layoffs and store closures. Those on the top 10 list, on the left, are expanding. InMarket says that the data are predictive of future layoffs and closures. Accordingly, Nine West and Disney should be next.

Customer loyalty (visitation frequency) is obviously a function of a number of variables. However, this kind of data can be used by investors to predict quarterly earnings or by retail corporate as an early warning signal of trouble. Indeed, store-visits data has utility beyond attribution.

It can also be used to measure and benchmark performance of individual stores across chains to find outliers and determine which stores to emulate or close. Foursquare, PlaceIQ and others have also promoted the benefits of location data for a broad array of uses beyond attribution.


Contributing authors are invited to create content for MarTech and are chosen for their expertise and contribution to the martech community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. The opinions they express are their own.


About the author

Greg Sterling
Contributor
Greg Sterling is a Contributing Editor to Search Engine Land, a member of the programming team for SMX events and the VP, Market Insights at Uberall.

Fuel up with free marketing insights.