Visually Compelling Maps Breathe New Life Into Retail Data

Visually Compelling Maps Breathe New Life Into Retail Data

Visually Compelling Maps Breathe New Life Into Retail Data

"Location" is a vital data point for just about every type of retail event, from the precise place a mobile purchase is completed to the real-time route of a delivery truck. Because location impacts so much of retail, displaying the data in a map format can facilitate decision-making capabilities across the enterprise.

Conversely, when information is delivered in just numbers or words, via a table or spreadsheet, "patterns of data can be elusive," said Gary Sankary, Retail Industry Manager at Esri. "But if you drop the data into a map with fairly simple symbology, it provides an instant spatial reference to data that makes interpretation easier and faster. This type of visual data mining is something that maps have excelled at for centuries."

Speaking on the December 7 Retail TouchPoints webinar, titled: Visual Data Mining: Making Sense of Big Data Quickly and moderated by Editor-in-Chief Debbie Hauss, Sankary made the case that To ensure a retailer is executing strategies in the right place and the right time, you need all three data entities."

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Making sense of data quickly always has been a priority, and it's one that will grow even more important as the Internet of Things (IoT) boosts data volumes even further. "Data from smartphones, smart cars and smart sensors represents a tsunami that's still off shore, but it's coming," said Sankary. "Retailers need to prepare now for when it hits, with offers, engagement and apps that are even more relevant to customers."

Social media also is a fast-growing source of "unfiltered data about your products and store, which can be terrifying — but valuable," Sankary added.

Sankary and his colleague Robby Deming, Marketing Program Manager at Esri, provided several examples of how using maps generated by a GIS (Geographic Information System) can quickly identify the most important questions a retailer faces, particularly when the maps combine multiple data sources. For example, a map showing the trade area for an urban store, combined with data revealing that many customers shop every day but only make small purchases, confirms that these shoppers are arriving on foot and carrying bags up to their apartments. "This retailer might want to offer a better product mix, by stocking quantities that offer a smaller number of items per unit," said Sankary.

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A map displaying where customers were when they made mobile or online purchases could help retailers identify how effective a mobile coupon would be at getting these shoppers into a brick-and-mortar store.

 



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