Before you buy anything online, e-commerce stores already have a pretty good idea of what you want.
And in the new and increasingly popular game of data gathering, Retention Science Inc. has positioned itself as a private eye for online retailers. The Santa Monica firm sifts through millions of data points that a store’s customers leave across the Internet then suggests ways to keep the customers coming back.
Those suggestions can come in the form of customized offers, tailored marketing campaigns, even the time of day a company will email out a promotion.
Retention, which late last month announced an infusion of seed money from San Francisco’s Forerunner Ventures, has now pushed its initial funding round past $2 million.
The marriage of big data and e-commerce is one that’s been attracting some interest from major retailers. Earlier this summer, Wal-Mart Stores Inc. acquired Inkiru Inc., a Palo Alto startup, to shore up its big-data prowess. And though Retention is sitting on a healthy round of seed funding, one of its closest competitors, New York’s Sailthru Inc., has pocketed $28 million in venture capital.
So far, Retention has worked with such stores as Santa Monica subscription e-commerce site Honest Co. and Louisville, Ken., custom apparel maker CafePress Inc. Company executives said they were also working with some big-box retailers but were not at liberty to disclose names.
Retention co-founder Jerry Jao said the game for his clients isn’t about attracting new customers. Rather, it’s about using massive pools of data and algorithms to get a client’s existing customers buying more stuff more frequently.
Forget the comment cards or feedback surveys, the new way customers chat with stores might be from the things they don’t even know they’re saying.
“Data help businesses understand their customers way better,” Jao said. “It’s the basic way of understanding how exactly they can talk to them.”
Of course, it doesn’t come cheap. A client can expect to spend roughly $100,000 a year for the service.
Retention is part of a new movement of tech companies that are trying to wrangle troves of personal data into a business plan. It’s a movement buoyed by the growth of broadband Internet and the decreasing cost of computing power.
Stores have long been pushing items based on previous purchases – think of the “recommended items” section that Amazon.com uses on its website.
But the uptick in big data has taken the strategy into surprising new areas. What about rearranging items on a webpage based on the price a store thinks you’d be willing to pay?