Analyzing consumer behaviour with location-based data in retail

This article was made possible thanks to our sponsor, Maptive, a leading mapping software provider.

Location data: definition and significance

Location data is all information that identifies a person, device, or object’s physical location. It is usually collected via GPS, wi-fi, or cellular towers and can be used to analyze consumer behaviour.

Location data include foot traffic, mobility, and more. Modern mapping software can help understand frequently used routes, traffic patterns in a location, peak traffic times, and more.

This data is worth analyzing if you rely on foot traffic to your retail location. Foot traffic has been decreasing consistently since the pandemic broke out in 2020. It dropped by as much as 51% during the worst months. The numbers increased in 2021, but the totals were still down by 5% for outdoor retail centres and 11% for indoor shopping malls.

In the second half of 2022, foot traffic declined again, ending the year at roughly the same levels as the previous year. In March 2023, foot traffic to brick-and-mortar retailers dropped by 5% year-on-year.

Location data analysis in action

A very crowded area of a retail store indicates that’s where the most-demanded and popular products are located. This data can help arrive at conclusions about product placement and potentially increase sales.

Map software might show a high number of seafood restaurants in an area, suggesting people in that area love seafood or a lot of people from seaside towns live there.

The retail giant Walmart, which has hundreds of locations across the US, was able to identify buyers who were close to the locations and deliver personalized ads in real-time. For example, they would send somebody who was walking by a Walmart store an ad on their mobile device with a special offer for that specific location.

Likewise, they would send promotions or ads for related products to customers who had recently visited a store based on their purchase history. They were able to drive sales by increasing foot traffic to their stores. Their use of location-based data created a more engaging and personalized shopping experience. This is crucial, as the experience with a company is just as important as its products, according to 80% of consumers.

As of July 2024, the retail giant’s revenue has increased by 6%, its operating income has increased by 32%, and its returns on advertising amount to 28%.

Why analyze consumer behaviour?

Retailers should use data to analyze competitors in the vicinity and understand local consumers’ profiles. This will help reduce the risks when selecting a new store location. Store owners can market new products or place best-selling ones in spots with high dwell times.

This approach is best complemented with online support, as 82% of consumers today expect their questions to be answered immediately.

Applications of data analysis

Retailers can use mapping software to retarget consumers who have seen outdoor ads on their mobile phones. Location data helps create targeted campaigns based on demographics. This approach has proven useful in retail and e-commerce: digital ads targeted at specific age demographics can lead to a 200% increase in click-through rates.

Retailers will find out who visits competitors’ stores, if a same-brand retail location is cannibalizing an existing one, or view and compare a competitor’s trade area. They can analyze the routes visitors take to a store and detect potential issues or changes in visitor activity.

FAQ

How does location-based data help retailers target customers?

Map software can analyze parking data, customer behaviour, etc. Based on this information, retailers can identify market gaps and opportunities.

What is one surprising benefit of mapping software for retailers?

Mapping software lets businesses see and compare competitors’ locations. Interactive solutions enable retailers to manage warehouse space efficiently.