advertisement
advertisement
advertisement
Created For and Commissioned By: ESRI
  • esri

How location intelligence is transforming retail

For smart sellers, those who know where their customers are will win the “location revolution”

How location intelligence is transforming retail

Winter has come for traditional retailers, right? Not quite. Recognizing their most potent advantage—knowing the power of place—smart store owners are turning to a combination of geographic information systems (GIS), Big Data, and artificial intelligence to discover new insights. Whether it’s using drones for site selection, tracking the latest viral sensation, personalizing prices, or mapping the potential of future stores down to the sales per square foot, retailers now have a new suite of tools at their disposal that go far beyond coupons.

advertisement

Here are five ways that location intelligence is revolutionizing retail:

1. DRONE-BASED SITE SELECTION

Once, rival retailers would count the cars in each other’s parking lots, using this crudest of metrics to gauge the health of their business. Today, competing chains are more likely to launch drone-mounted cameras, using machine vision to identify makes and models. “Imagine a retailer who can then fuse this with demographic information,” says Mansour Raad, a senior software architect and Big Data lead at Esri. “What kinds of cars are in the lot? Mercedes? Toyotas? It’s the fusion of those things that is interesting.” Knowing household incomes is one thing; knowing which of those households are at your store right now is something else altogether.

2. PREDICTIVE SHOPPING

Five years ago, Walgreens launched its annual “Flu Index,” which measures influenza outbreaks across America using the chain’s retail prescription data for antiviral medications from thousands of pharmacies. Its weekly maps are more current (and thus more accurate) than even the Centers for Disease Control and Prevention’s. But the flu isn’t the only thing to go viral. Retailers are mining sales data from their own locations to spot historical sales patterns and predict future best sellers at each location, offering them a jump on kick-starting their supply chains and tailoring the mix for every store shelf. Individual stores of national chains may never look identical again.

3. PERSONALIZED PRICING

Dynamic pricing is nothing new (have you purchased an airline ticket lately?), but setting a price on individual demand and behavior is rarer, and much harder. Leaving money on the table through low prices can make or break a company. For example, PwC has found that a price increase of 1 percent typically results in an 11 percent spike in profits. This is especially true in insurance, where a failure to accurately price risk can lead to catastrophic losses. Traditionally, insurers have turned to historical data to set premiums accordingly, which is why young, inexperienced drivers are penalized regardless of caution. But a combination of in-car telemetry data, location intelligence, and personal data will make it possible to tailor premiums according to how they’re driving—minute-by-minute and down to the mile. “Every company I speak to is pursuing moment-by-moment premiums,” Raad says. “One wanted automakers to install a set of green, yellow, and red lights on the dash to warn them about their driving.”

4. HALO FORECASTING

Brick-and-mortar retailing isn’t dead—not when having a local store can boost online sales 20 to 30 percent in the surrounding area. This phenomenon, known as the halo effect, has the potential to transform site selection, but only if retailers are able to precisely map the performance of existing stores and predict the potential of future locations. Halo forecasting combines location intelligence, transactions, consumer profiles, and AI to predict how local in-store and online sales will affect the other. In practice, this means melding drive times, demographics, competing and complementary amenities, and online and mobile purchasing habits to understand the role space plays in sales. Store proximity matters more—not less—than ever.

advertisement

5. GROWTH HACKING

Predicting where to open your next store is one thing, but what if your plans call for opening 1,000 in the next six months? That was the dilemma faced by X5, a grocery-and-convenience chain that has rapidly scaled into the largest retailer in Russia, with more than 13,500 locations and a market cap of more than $6 billion. Its secret was to combine a location intelligencedriven heat map of potential storesincluding predicted revenuewith an internal development road map shaped by the insights of hundreds of local managers. With this plan in place, regional managers are given the heat map and wide latitude to choose their next location—a structure that executives credit with accelerating the pace of openings by a factor of five.


This story was created for and commissioned by Esri.

advertisement
advertisement

About the author

FastCo Works is Fast Company's branded content studio. Advertisers commission us to consult on projects, as well as to create content and video on their behalf.

More