For its 80th birthday, Paul Stuart got a functioning customer database.
The database serves as the foundation for the company’s revamped marketing strategy. The goal was for the retailer to first understand who its customers were, how often they shopped and what products they tended to gravitate toward. This information goes far beyond what it formerly knew about customers, which was limited to average order value. From there, the company divided its full customer base into segments, slicing and dicing by factors like purchase behavior and style profile, and then used machine learning to revamp what customers received which email newsletters and Facebook ads, and how often.
“When I joined, there was no digital advertising,” said Jessica Granata, the director of digital marketing and CRM at Paul Stuart, who joined the company from Brooks Brothers in January 2017. “There were a million things to do. We didn’t have much of anything in terms of CRM. We couldn’t identify customer life-cycles. It wasn’t in good shape. But it ended up being kind of great, because we could only go up from there.”
Paul Stuart, which has a smaller women’s business, a wholesale line and a younger, more modern brand called Phineas Cole, specializes in tailored clothing that start at $2,000 each. It’s an aging heritage retailer, and CEO Paulette Garafalo, who joined the brand in 2016, was tasked with recruiting new, younger customers, building up the wholesale, international and women’s businesses and fleshing out the made-to-order business online.
For legacy luxury brands overall, reconfiguring business strategies to align with, and keep up with, changing customer behavior is a mounting challenge when old processes no longer fly.
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“Luxury brands come from a world of having a ‘mega brand’ built on superior design,” said Pini Yakuel, CEO of Optimove, the marketing platform Paul Stuart used. “Their marketing strategies are not built to scale or move at the speed of the customer. So access to customer data is really poor; they have dispersed offline and online data, and, as a result, they suffer from the time of ideation to execution. Some brands are now realizing they need to change this approach.”
For Granata and her team, the goal was simply to drive more sales through digital marketing. To do that, the customer database combined online customer data with data from store sales associates to define customer style profiles and behavior. Like most fashion retailers, Paul Stuart’s most effective digital channel is email marketing, so Granata focused there when thinking up new messaging strategies shaped by the customer insight culled in the data. For instance, she said, customers (and especially the younger Phineas Cole customers) responded particularly well to styled “lay down” emails, where new products are shown arranged in the form of outfits. The marketing team worked with the merchandising team to create several versions of that product display to send to different customer segments, depending on their likelihood to buy into a certain style.
Granata was also able to carve out a list of core customers from the mass customer database, targeting those who shop most often and respond to email pushes most often. By segmenting out customer groups and personalizing messages accordingly, Granata said email open rates tripled, on average. Whereas mass emails might dip as low as a 10 percent open rate, targeted emails saw between a 20 and 50 percent open rate.
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“The marketing team, while small, has 100 percent changed the way it works in the past two years. We’ve gamified our approach, in a way, where we can continually have new ideas, test different combinations and send to more customers,” she said. “It’s kind of fun, in that you get your results pretty instantly — that’s the beauty of digital.”
Smarter email messaging is also playing a key role in pushing more customers to shop both in stores and online, which increases their lifetime order value. Granata said the team has laid out a three-part email series for customers who have only ever shopped in stores: After one in-store purchase, they’ll receive an email listing off online ordering benefits, like free returns and shipping. If the customer’s next purchase is again made in store, the next email gets more specific, by going into exclusive online products and features like live chat and the content blog. After three consecutive in-store purchases, the customer will get an email with a 15 percent-off code, exclusively for online orders.
Conversely, customers who shop exclusively online will get a series of emails about the in-store experience and then, if necessary, a promo code.
“We’re not overly promotional, but at the end of the day, we want that cross-channel customer,” said Granata.
Data is also feeding back and forth from the in-store and online channels. Store stylists, who Granata pointed out are often decades-long employees, will receive online-supplemented data regarding their client lists, so they can see what they’re purchasing or browsing online. The company is in the process of creating a more detailed in-store database based on the information stylists collect, which Granata said will be used to both better inform the overall business and push offerings to new customers.
Using machine learning, Granata has also been able to identify the company’s biggest hurdles, like one-time purchasers, and figure out how to bring them back in for a second purchase. Yakuel said the goal is to free up time for fashion brands to focus on creative marketing strategies, not spreadsheets.
“For a heritage brand, that heritage is invaluable. A machine doesn’t get that,” said Granata. “But we can use this data to better understand that intangible quality that has made Paul Stuart last for nearly 100 years: Why do our customers continue to come here and spend money like they do, and how do we recruit a younger customer without straying too far from our original brand message?”
