NextTech: Mapping ‘Human Weather’ Patterns with Geospatial Analysis

The pandemic has reshaped consumers’ shopping, eating, and entertainment habits—and rerouted the rhythms of our daily lives.

The office worker who’s no longer commuting isn’t frequenting her favorite downtown corner café; instead she’s heading to a suburban chain coffee shop with a drive-through window. A father and daughter have forgone after-school ballet classes in the studio in favor of yoga classes in the park. Families stuck in the house are diving into home improvement projects and visiting big-box stores that offer a seamless omnichannel experience, complete with curbside pick-up.

Data scientists call the sum of these movements “human weather.” It represents the spatial patterns and routes—revealed in anonymized location data from smart devices like phones—that area residents follow as they work, play, and shop. Businesses have long studied meteorological reports to shift supply chains around natural disasters or stock up on products like salt and shovels in advance of a winter storm. Similarly, human weather patterns help executives interpret and respond to trends in customer behavior. And few events have changed consumer behavior as profoundly as the COVID-19 pandemic.

One technique for making sense of human weather is geospatial analysis, which combines the pattern-finding ability of big data analytics with the location context of GIS, a geographic information system. Data-savvy companies are embracing the insight created by geospatial analytics—a type of location intelligence—as a way to serve customers where they are, even in light of the dramatic changes triggered by the pandemic.

Location intelligence can inform business decisions such as what hours to keep, which amenities to offer, and how to advertise—choices that can help companies engage customers in an era of social distancing and touchless retail. Especially when layered with demographic or behavioral insight, geospatial analysis can help a company create continuity in the midst of a historic economic challenge.

Where Have All the Customers Gone?

The video below shows a geospatial analysis of human weather in a hypothetical scenario, revealing pandemic-related changes among visitors to an outdoor resort. The analysis begins with a directional distribution of customers, identified by the orange ellipse. This shows the general area where customers live. Using geospatial analysis, a location analyst can then identify the counties where business is down, with darker blue areas indicating steeper customer declines.

Adding a layer of data helps an executive understand the context of those broad trends: orange dots indicate generally how many people from that region are visiting the business. With that insight, a sales manager can better calibrate the threat posed by drop-offs from visitors in specific areas.

For instance, a county might show up as dark blue, signaling a point of concern, but feature a smaller orange dot, revealing that the number of customers hailing from that county was already minimal. Meanwhile, a big decline from a densely populated region like Seattle might indicate an opportunity for corrective measures like increased marketing and promotions.

Laying the Groundwork for Targeted Growth

As the analysis progresses, a geospatial perspective makes it possible to incorporate key insights about consumer behavior and location that, when transposed with pre- and post-COVID activity levels, yield powerful conclusions.

In the hypothetical analysis, movement data shows that three demographic groups account for the biggest declines in visits: Green Acres, or self-reliant types from rural enclaves; the Great Outdoors, which includes active empty-nesters; and Savvy Suburbanites, comprising wealthier older couples. As the map shows, these groups tend to cluster in various ZIP codes and block groups (the smallest geographic unit used by the Census Bureau).

Executives might focus on winning back these groups once the pandemic recedes. With location intelligence, business leaders can craft a strategy that speaks to those customers’ unique preferences, targeted in their specific regions.

Budget for TV and radio advertising could be concentrated in the areas outlined in the map, paired with a direct-mail campaign offering discounts or other incentives. Executives could also expand hours and tailor prices and amenities to suit the lifestyle habits of people in the three groups, who are largely at or approaching retirement age.

Other layers of information such as the penetration of vaccine distribution, or sales at restaurants with outdoor seating, could signal places where customers are starting to reengage with pre-COVID recreational behaviors.

Just as important as knowing where a business has lost customers is knowing where it hasn’t. This geospatial analysis technique can map the demographic and psychographic groups that will keep coming back to a venue no matter what. Leaders can take necessary steps to maintain this core customer group while dedicating more aggressive measures to growth customers or niche customers.

Staying Ahead of the Human Weather

Geospatial technology could be leveraged across industries to give companies and small businesses direction on how to mount a post-pandemic comeback. Grocery store executives can analyze human weather to track whether certain customer groups have transitioned to lower-cost chains, and retool practices accordingly to win them back.

A fast-casual restaurant could redraw its delivery area to recapture once loyal in-person customers who spent the most. A newspaper or media agency might use geospatial analysis to identify customer shifts for advertisers, and recommend adjustments to ad targeting.

Many companies analyze core customer or non-customer groups when they first enter a market, then neglect to revisit the data and findings. A disruption on the scale of the pandemic shows why it’s smart to know who a business’s customers are and where they’re coming from, especially as times and people change. The location intelligence delivered by human weather and geospatial analysis puts those changes on the map.

About the authors

Gary Sankary joined Esri in 2014 as a subject matter expert in retail after spending 30 years in the industry. Gary’s retail career started in his parent’s family business more than 40 years ago. Along the way he had an opportunity to work with Cost Plus Imports, Mervyn’s and Target Corp. where he led a number of cross-functional teams developing technology and business process strategies to support store and digital merchandising initiatives.

Joel McCune is fascinated by the power of geographic data-driven decision making. Through his work at Esri, he helps companies uncover innovative insight by applying quantitative methods that marry the power of geography and data science.

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