Leveraging Big Data to Boost Click-Through Rates Retention Science uses predictive algorithms to create automated marketing campaigns for companies based on customers' buying patterns.

Back in 2012 SwayChic.com, the e-commerce site for Northern California-based casual-apparel chain Sway, was struggling to get the customers in its database to buy more. No matter what it tried, its e-mail marketing efforts fell flat, averaging a dismal 11 percent open rate and 0.9 percent click-through rate--numbers that were well behind the retail industry averages of 31 percent and 3.4 percent, respectively, according to e-mail marketing provider MailChimp.

"It was really trial and error," says Cheyanne Sequoyia-Mackay, SwayChic's project and marketing manager. "We were looking for a smarter way to send e-mails without having to put so much research into it."

The Fix
SwayChic enlisted the help of Santa Monica, Calif.-based Retention Science, which leverages predictive algorithms to create automated marketing campaigns. For a fee (undisclosed) based on the size of SwayChic's customer database, Retention Science integrated its software with the retailer's e-mail blasts, then analyzed the data, evaluating more than 300 customer behaviors such as purchase history, when they opened e-mails and when they visited the site. Armed with that information, Retention Science gave SwayChic a precise schedule, down to the day and hour, when targeted segments of its database were most likely to open and act on e-mail pitches.