eBay has incorporated machine-learning algorithms into its marketing outreach to personalize email messages and display ads.
Alex Weinstein, director of marketing technology and CRM at eBay, discusses his company’s email marketing overhaul in a Q&A with eMarketer.
“We understood that we needed to reinvent our strategy to be more customer-focused and treat each customer as an individual, rather than a member of a group [of millions],” states Weinstein. “That’s why we decided to invest quite meaningfully into a one-to-one personalization platform. We created an approach where humans make the creative and the raw materials, but machines do the personalization.”
eBay has built an in-house personalization platform that now allows the company to incorporate real-time data into campaigns to promote offers that are most relevant to the end user. Each email newsletter now sent by eBay is evaluated with a machine-learning model that recommends relevant promotions and products based on a customer’s browsing history.
Previously, eBay’s email marketing strategy was largely batch-and-blast ad-hoc emails.
Almost half of email marketers still send their subscribers the exact same email, according to a recent study by GetResponse, but batch-and-blast campaigns are largely ineffective. Irrelevant emails are more likely to be marked as spam by subscribers, and this is one of the leading causes of unsubscribes.
Email is a channel where subscribers have opted-in to receive marketing, and customers have requested to receive news and promotions because they are interested in the brand or organization. Personalization is critical to capture this interest and convert it into long-term loyalty, so it isn’t surprising that more than 90% of marketers polled by VB Insight asserted that incorporating personalization into their email marketing improved customer engagement.