I had the opportunity to attend the Esri user conference last week in San Diego, California.Esri may not be well known to retailers, but I suspect that what it does will soon be a hot topic in the industry.Esri (short for “Environmental Systems Research Institute “) is a 49-year-old company that offers a GIS ( “geographic information system “) analytical platform to help organizations use “digital geography ” to understand the physical world better. For example, the company has made big inroads with both governmental and non-governmental organizations in their use of spatial analytics to better understand how human activity impacts the environment.

Many of us already use some kind of dynamic geo-spatial information (if you have an on-board mapping system with traffic alerts in your automobile, you use it). There are many commercial uses for spatial information as well, and Esri is among those companies that think that the time is right for the retail industry to consider the use of dynamic geo-spatial data to optimize their operations.

Of course, geographical information isn’t new to retailers. In fact, companies have been enriching maps with demographic and psychographic data to plan store locations for many years. But because of new geo-location data generated principally by mobile internet-connected devices, it is possible to dynamically link current customer flows in and around current locations to spatial information, to help retailers with merchandising decisions, as well as site selection for both stores and distribution centers. By analyzing the geo-location data generated by mobile phones, retailers can be armed with far more accurate and up-to-date insights about where people come from, where they go, and what they buy.

The question is, why would these new insights be important to retailers now? It all has to do with the disconnectedness between where demand is generated and where it is fulfilled in the Omnichannel retail environment. Here’s what I mean by that:

Retailers have made decisions about what products to sell, where, and when, by analyzing sales data by Product (what sells), Time (when it sells), and Location (where it sells). These are the dimensions of the “data cube ” that many retailers have used since item level POS scanning became de rigueur in the late 1980s. You’ll notice that there isn’t a dimension called “Customer ” in that data cube. The truth is that retailers didn’t really need to know very much about how the consumer came to a purchase decision, since it happened within the physical four walls of the store.

By the same token, retailers didn’t have to worry too much about how the product got into the hands of the consumer. Especially in the self-service environment perfected by big-box mass merchants and supermarkets, product went from the shelf and into the shopping cart. The customer did all the work. Therefore, POS scans were a perfectly reasonable metric both to determine demand and to position supply. But nowadays, where and how demand is triggered and where and how it is fulfilled are physically disconnected, and not easily observable. That’s why location data is going to become a big thing for retailers.

RSR conducted a benchmark study in December 2017 to uncover the extent to which retailers have interest in what one might think of as the digital overlay to their physical world – the locations, the products and processes within those locations, and how people interact with those locations.

When we asked retailers to identify the most important capabilities geo-location data and analytics could enable, there was very little that retailers weren’t interested in pursuing – at least when it comes to connecting with consumers (Figure 1).

Figure 1: Reaching Customers Directly

Source: RSR Research, December 2017 

But in spite of the enthusiasm that retailers expressed for using location data and analytics to interact with consumers in new ways, there’s little evidence to suggest that geo-location intelligence has become the new normal for retailers. It is still very early days when it comes to location analytics in retail. In fact, the benchmark showed that many retailers are holding back, waiting for a clear ROI to emerge.

And that brings me back to the Esri user conference. In one presentation, Dr. Thomas Horan of the University of Redlands (California) “Spatial Business Initiative ” disclosed the results of a just-completed study the initiative undertook to understand how businesses are adopting location analytics. The study noted that two patterns are emerging: (1) a growing understanding of “Location value “, and (2) a “spatial maturity ” model – emerging patterns in how businesses are driving value creation with location analytics. The professor noted that high performing organizations are analyzing customer spatial patterns to optimize business performance (a retail-specific example might be in understanding the radius of influence of a store when it comes to online customer order creation).

In another presentation, Sheila Davis, IT Manager of Fedex Services, described how the carrier is using spatial analysis for map visualization and search, and travel analysis & optimization, to optimize package delivery services. And in a third presentation, Paul Rossi, Supply Chain Specialist at General Motors, described how the auto manufacturer is using GIS information to enable visibility into its supply chain sub-tiers to better understand and manage supply chain disruptions.

Both the Fedex and GM presentations have direct applicability to the retail industry; one clearly related to the supplier-side of the business, and the other having to do with profitable fulfillment of direct-to-customer deliveries. While the ever-expanding network of global sources isn’t a new challenge for retailers, it’s one that is getting more attention nowadays (at RSR, we’ve been able to detect a clear uptick in interest about product lifecycle management solutions by retailers concerned about environmental and workplace standard compliance by offshore sources). And as the number of direct-to-consumer shipments from fulfillment centers and the stores increases, retailers have to be thinking about optimizing “last mile ” deliveries in order to preserve the profitability of those sales.

Supply chain visibility and customer order delivery optimization are just the tip of the iceberg when it comes to the potential usefulness of geo-location intelligence. Digital marketeers already know the value of using geo-location information to target content to consumers, and retailers are thinking about proximity marketing within the four walls of the store. Some retailers are using geo-location data generated from consumer mobile devices for in-store wayfinding applications and in-store traffic analysis.

It seems likely that just as retailers are getting religion about using “outside ” non-transactional information (like competitor promo data, micro-market specific data, and weather data) to localize their offerings and optimize their operations, more retailers will find value in geo-location intelligence as well.

And that’s why it well may be the “next big thing ” for retailers.