In RSR’s February 2019 benchmark study on the state of geo-location intelligence in Retail, we stated that:

“Location-based intelligence is enabled by two things: the geo-location data created principally by consumer smart mobile devices, and new analytical tools associated with ‘big data’. Analysis of location data can be used for several reasons – to pick the best physical sites for stores and distribution/fulfillment centers, to optimize direct customer delivery routes, to better understand local markets and the people that live and work in them, and most importantly, to be able to reach customers wherever they are via the mobile channel.”

We’re not alone in that assessment. Academicians, technology companies, and retailers all see the potential, and at least for now are open to sharing points-of-view and ideas. For example, last week the University of North Texas Department of Geography and GIS (‘global information system’) technology company Esri  co-hosted a meeting in Dallas with retailers and other technologists to discuss the possibilities and perils associated with the use of geo-location data and analytics to improve business processes and outcomes. It was a great opportunity to learn about how organizations are trying to use geo-location data and analytics in the real world.

After UNT’s Global Digital Retailing Research Center Senior Director Linda Mihalick kicked off the meeting, Esri’s Gary Sankary outlined his company’s view of the value of geo-location data and analytics: “understanding WHERE”, “determining RELATIONSHOPS”, “measuring SIZE, SHAPE, and DISTRIBUTION”, finding BEST LOCATIONS, BEST ROUTES”, modeling & PREDICTING OUTCOMES, and “detecting and quantifying PATTERNS”. The speakers that followed explained how that value can be realized.

Real World Use Cases

Ulta Beauty’s Data and Geography Systems Manager Ralph Torres discussed how Ulta is using customer behavioral data to determine customer segmentation strategies, which in turn is driving localized assortments and helping the retailer determine which localized services should be offered. Ulta uses location attribute data to provide fully automated analyses to its decision makers. Those analyses include market overviews and comparisons, retail comparisons, competitive summaries, and market analytics, all delivered in a highly visual format.

Harbor Freight’s Senior Spatial Analyst Matt Niblett shared how the company uses GPS data to measure customer satisfaction and to optimize last-mile logistics. And UberMedia’s Vice President Data Sales Christopher Smith explained how fast food retailer Sonic Drive-In is using geospatial analysis to make better site selections. As an example, Chris shared how geospatial analysis can help Sonic decide which one of six local sites can be closed without losing customers, based on an understanding of consumer driving patterns.

In one of the most revealing (if somewhat alarming) presentations of the day, Dstillery’s Senior Geospatial Analyst Peter Lenz revealed both how his company uses geo-location data to analyze consumer brand engagement as relates to online ads. Peter shared how geo-location data can be used to relate devices (for example, a consumer that uses an iPhone, an iPad, and a desktop) so that advertisers can offer consistent value messages across those devices. But Peter also shared how bad actors can “spoof” systems with false or stolen GPS data. For example, there are offshore hacking factories that successfully divert ad money by faking traffic to particular online ads. According to Peter, up to 20% of ad monies associated with online ads are at risk from this kind of fraud. To get a sense of how much money that represents, the total U.S. ad spend in 2018 was $151 billion [1] ! GPS spoofing can also be used to make it difficult for retailers to get a true representation of the traffic patterns around current of proposed store sites – making it difficult for those retailers to understand stores’ radius of influence. Why would someone do that? “Corporate misbehavior” comes to mind….

Guidance

The symposium’s afternoon was devoted to how companies can begin to get value from geo-location intelligence. Retail Scientifics’ managing partner Shawn Hanna and Dr. Jonathan Wilson discussed how geo-location analytics can be used to improve Market Planning, Pricing, Marketing, Forecasting, Assortment Planning, and to understand “the Voice of the Customer”.

Esri Spatial Data Scientist Joel McCune shared how geo-location analytics can be used to examine trade area dynamics to understand issues like the cannibalization effect of multiple store locations, comparative market performance, and how geographic factors can affect store performance.

Why This Dialogue Is Important

At the beginning of the day, UNT professors Dr. Murray Rice, Ph.D. and Dr. Judith Fornay, Ph.D. explained that the school’s program is designed to be “curious, creative, diverse, and focused on pragmatic problem solving”. This was the spirit of the day, and given the relative newness of geo-location analytics to the Retail industry, it’s entirely appropriate that practitioners, scholars, and technologists openly share the possibilities associated with the new data and analytics. It’s still early days when it comes to geo-location intelligence.

But the time is now for such an open sharing of ideas. Everyone concerned needs to understand that over-performing retailers (that we call “Retail Winners” in our studies) are already figuring out how to use geo-location analytics as a competitive wedge. Our February study concluded that, “<Winners> anticipate that this singular asset will provide them information to make smarter decisions about the products they sell, which stores those products go to, where within the store they have the most effect, where employees should be, what those employees should be doing, where customer-facing messaging and promotions should go – the lot of it.”

So we applaud UNT and Esri for sponsoring the symposium, and hope that other organizations will follow suit. But as with every information technology that can be turned into a competitive weapon, there’s only a short time frame before geo-location analytics becomes a baseline capability for successful retailers.