As economies worldwide roar back after 2022’s downturn, retailers are looking for ways to capitalize on a flurry of new consumer activity. Armed with insights from the bumpy years of the COVID-19 pandemic, many are turning to data-driven strategies to shore up their customer base and find new markets.
One important tool for driving retail growth is location data. This category of data enables companies to pinpoint the positions of individuals, devices, and points of interest (POI). Companies of all kinds are tapping into the benefits of different kinds of geospatial data, including POI data (physical sites such as restaurants, stores, parks and other landmarks) and mobility data (itself anonymized and aggregated from devices of all kinds).
Let’s take a deeper dive into how geospatial insights are enabling retailers to get smart about site selection, personalize advertising efforts, and develop competitive intelligence, all benefits that can turbocharge recovery efforts and help retailers gain efficiency in challenging times.
Get Smart About Site Selection With Geospatial Insights
Location data is a catalyst for retailers that want to conduct market research and strengthen their expansion strategy. This is especially crucial for companies growing quickly or expanding into new international markets. However, retailers should be risk averse in the site selection process, as investing in the wrong site for a new location could cost the company thousands or even millions in lost revenue. However, applying geospatial insights in the market research process and using verified data to strategically select new sites can set retailers up for success.
For example, the German-based supermarket chain ALDI might use geospatial insights as part of its expansion efforts in the U.S. In 2022, Florida, Texas, and the Carolinas (North and South) saw the highest rate of domestic migration. ALDI could zero in on cities and suburbs with the most growth in those states and use location data to identify potential sites based on POI and mobility data.
ALDI might look for shopping centers in those areas which see high levels of foot traffic, lease retail space to brands that serve their target demographics and don’t currently host a supermarket chain. At the same time, they may also use location data to investigate where their competitors are in proximity to the prospective sites, as well as the amount of traffic flowing to those competitors and other POI nearby.
Use Location to Personalize Advertising
If geospatial insights are strategically leveraged, retailers have a myriad of options for reaching shoppers and increasing revenue — both in and outside of the physical store.
POI and mobility data again come into play for retailers seeking to increase the return on investment of their advertising campaigns. Outside of the physical store, retailers can use geospatial insights to tailor their out-of-home (OOH) media buying strategy. Data collected from mobile devices show the flow of individuals into, out of, and around POI. These datasets provide reference points for retailers buying OOH ad space in that area. Retailers might also activate a geo-conquesting campaign, delivering targeted mobile ads to users when they’re within range of a competitor.
Once a consumer is inside of a retailer’s store, the ad targeting continues. Through geofencing, shoppers can be tracked as they navigate through a store and receive highly targeted ads for products based on their location.
For example, ALDI might partner with Mama Cozzi’s Pizza Kitchen on an in-store ad campaign. Part of the campaign strategy includes location-based mobile ads to promote the frozen pizza products to customers who are in aisles with tomato sauces and dairy products. When a customer with the ALDI mobile app pings a beacon in these areas, they’re served a push notification with an ad and mobile coupon for the pizzas.
Develop Competitive Intelligence to Capture Market Share
Even if retailers aren’t looking to expand into new markets, they can use geospatial insights to analyze their current market and uncover opportunities to outperform their competitors.
Based on their target demographics, retailers have an opportunity to research the most complementary POIs for partnerships. By combining POI data with mobility data — which reveals crucial insights into consumer habits — retailers can invest greater resources into developing partnerships that will increase brand awareness among their target audience and boost sales. They can also get a sense of which POIs may already be partnering with their competitors.
For example, a specialty foods retailer serving the Philadelphia area, Di Bruno Bros, could seek to increase sales from weekday commuters in its Wayne, Pa., location. Knowing that the store is located less than five minutes away from a SEPTA train station, and that this line is heavily utilized by commuters into and out of Philadelphia, Di Bruno Bros could use location data to find out which businesses commuters are patronizing after deboarding the train. They could then use this data for advertising efforts, such as geo-conquesting and OOH, or to develop a partnership strategy with noncompeting businesses that attract the SEPTA commuters in that area.
Location data also enables retailers to evaluate a competitor’s ebb and flow of foot traffic and their visible presence. They can then transform this information into a plan to address potential sales and marketing gaps. However, datasets aren’t universally applicable. Geospatial insights should be gathered with a clear goal in mind and executed through the most relevant and accurate dataset.
Complete the Strategic Puzzle With Location Data
The use cases for location data don’t end there for retailers. It plays an integral role in optimizing supply chains, identifying opportunities for targeted merchandising, and even revealing an area’s consumer spending potential. It also means that retailers will need processes for gathering, analyzing and applying different datasets, including POI, mobility and demographic data.
Finally, the most fundamental requirement of using location data in any aspect of retail business is data accuracy. Location data comes from numerous sources and can be available for free or purchase. In many cases, location data is unvetted and unverified for accuracy, leaving datasets rife with outdated or incorrect information. Retailers must be cautious about where and how they’re sourcing data.
Geoff Michener is the CEO and co-founder of dataPlor, a company that delivers the most accurate global point of interest (POI) data.
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