Leveraging Big Data to Boost Click-Through Rates
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."
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.
The e-commerce site's revenue tripled within the first two weeks of using Retention Science, according to Sequoyia-Mackay.
"And this was just from altering the way we sent our e-mails," she says. "It didn't include any stylistic changes."
The average open rate increased to 15 percent, and the average click-through rate more than doubled to 2.2 percent; some campaigns, such as a discount sale, achieved click-through rates of more than 10 percent. SwayChic's Cyber Monday promotion last November, for example, resulted in sales that were 400 percent higher than the previous year's.
Now Sequoyia-Mackay is experimenting with Retention Science's incentive-based campaigns, wherein targeted customers receive individually tailored promotions based on their previous buying patterns and other data.
A Second Opinion
Austin-based Bryan Eisenberg, a digital marketing expert at Iterate Studio, says it's easy to grasp the benefit of Retention Science. "Digital marketing is complicated; there are so many moving pieces on top of everything that's related to retail and e-commerce in general. Most retailers are way too busy for this," he explains.
However, he notes that it's a huge jump to go from essentially no data analysis to something as powerful as Retention Science. For some, a very basic approach may provide sufficient results--and at a lower cost. "You can go into your databases, and you can pull out every single e-mail and corresponding time of purchase, and you can create different customer buckets for morning, afternoon, weekend, weekday e-mails," he says. "That should improve your overall response rate."
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