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Before people began making their lives public on social networks, retailers had to figure out their likes more indirectly. Companies like Oracle and Siebel provided huge database programs that analyzed individual sales and consumer demographics in search of patterns that might lead to more sales—say, by targeting groups of customers who might be likely to respond to special offers. But the retailers couldn’t directly observe the connections between individual consumers, or watch them chat online with each other about products.

CalmSea, a company founded in 2009 by database industry veterans, adds consumers’ social-network activity to the mix of what retailers can analyze. Moreover, the company takes advantage of cheap large-scale database computing to crunch numbers nearly in real time, and to experiment on the fly with new analysis methods that would have required serious database retooling in the past. Clients include the sneaker company Puma and Tobi.com, an online clothing retailer.

“Retailing is changing,” says CalmSea’s vice president of products, Vivek Subramanian, himself a former engineer for Siebel’s analytics software. “We used to look only at data inside the enterprise. Today, there is a lot more data coming from outside the enterprise.” The primary source is Facebook, where CalmSea clients publish apps branded under their own names. An app for Tobi.com, for example, may offer an extra 10 percent off sale items; when someone uses the app, the client can see which Facebook pages for brands, products, or retailers the customer likes, shares, or comments on.

By giving each customer a unique promotional code, CalmSea can track who buys what. It can also see who a customer’s friends are, making it possible to identify groups of like-minded shoppers who may not even realize what tastes they have in common. The retail industry “used to look at past sales data on who bought Ralph Lauren jackets in April,” Subramanian says. “Now we combine that with the social graph of current activity. What are the most popular brands followed in their social network? Maybe it’s Calvin Klein instead.”

CalmSea calculates individual customers’ brand and product affinities, as well as their “promotion elasticity”—that is, how big a difference a discount makes in their propensity to buy a promoted product. Some customers won’t buy without a markdown. But even in the era of Groupon super-discounts, sellers are wary of giving everyone a price cut that might not be necessary. Price optimization is one of the reasons retailers spend big money on databases.

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Credit: Gabriela Hasbun

Tagged: Business, Business Impact, analytics, Understanding the Customer

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