Behavioral Data Gives Diesel a Fashionable Edge

 

It’s a common situation: A company has enough customer data to be fairly relevant, but its marketers know that with just a bit more they can get a view of customers that allows them to get, well, personal.

That was the situation Diesel faced when Dasha Gastol joined the fashion brand as digital marketing manager last year. “We had limited insight into our consumers,” she said to me when we met at Salesforce.com’s ExactTarget Connections conference. “We wanted to know more about their online behaviors and how we could market with more relvance.” Another goal was to bridge the gap between Web and email.

One solution, she said, was to implement ExactTarget’s Predictive Intelligence product. It allows Gastol and her team to see prospects and customers online and market to them based on their online behaviors, such as what they search for and which products they look at. “We can take that [behavior] data and use it to create personalize messages on our site,” she said. But that’s just the beginning. “We’re also going beyond only sending blast newsletters, which we still do for, say, new collections,” she added. “ Before, we couldn’t speak to [customers] in a cohesive way. Now we can embed personalized recommedations based on actions subscribers took on our website, which creates a connected experience.”

According to Gastol—and not surprisingly—these personalized recommendations online and in email campaigns are driving conversions. “All of our email metrics have gone up: opens, clicks, etc.,” she said, noting that personalization is also driving more engagement and discovery.

One approach especially has garnered unexpected results: rethinking cart abandonment reminder emails. Gastol and her team were surprised by the high engagment with abandon cart emails that show the cart items plus additional recommended items based on customer behavior. The Predictive Intelligence product is recommending especially relevant products, she said. Gastol noted that the tool is also useful for determining what not to show. For example, not promoting women’s products to men.

When I asked Gastol if there was one type of data that was most useful, she pointed to behavioral data as particularly beneficial. “Behavioral data has been most helpful to us. Behavior shows intent, which has helped us evolved our strategy,” she said, noting that purchase data is also important and useful for segmenting.

“For us it’s been an evolution,” Gastol added. “We wanted to get a granular level of data and start personalizing the customer experience; to create unique experiences for each customer.”

Today, Gastol and her digital marketing team are using that data to “understand the customer at the point of discovery.”

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