The In-store Impact of Customer Analytics

In 1890, Levi Strauss & Co. produced its first pair of 501 overalls, which were notable for the copper rivets that anchored stress points—such as on the edges of pockets—to reinforce the garment and prevent tearing. The overalls soon became the 501 jeans—Levi’s flagship product. The 501s are also versatile—they can be purchased for under $40 at a department store, or for $500 at Barney’s.

Recently, Levi’s’ analytics revealed that 501s had become immensely popular in urban communities—which influenced Levi’s messaging and stocking decisions. One retail partner that stocked Levi’s jeans produced 40% of all 501 sales in Detroit, said Tom Rafferty, Levi’s’ VP of global commercial planning, during a panel at the SAS Global Forum 2013 in San Francisco, CA.

“That’s where [analytics are] powerful,” Rafferty said. “Where we apply the product to the consumer and get information that lets you drive a successful business outcome.”

Levi’s was one of three brands—including J.Crew and Williams-Sonoma—whose representatives discussed the way in which digital channels and data strategies can both frustrate retailers and be a boon for their businesses.

Digital is about convergence

When retailers build a digital strategy, they need to think about more than just collecting information on a channel-by-channel basis. Sid Hamburger, senior director of supply chains at J.Crew, said that digital needs to transcend Web, mobile, and tablet elements. The end-goal should be using data to create a consistent experience, the model for which is what customers experience in-store.

“From data collection to transaction to experience, digital is all convergence,” Hamburger said. Being mindful of the converged customer experience across multiple channels dominates the way in which J.Crew develops its back-end systems, technological investments, and support systems for business partners.

For J.Crew, the goal is to increase its full-price sales and drive higher margins and quicker returns on inventory.

Build out a data strategy gradually

Levi’s Rafferty identifies a natural sequence as companies evolve their business practices around customer insights and analytics. The first, and possibly the most challenging, is simply developing a solid master data strategy. This means ensuring the necessary databases are validated and cleansed.

“As you move through, you can become more sophisticated as you successfully apply [customer analytics],” Rafferty said.

Admittedly, this first step can be a bear for some companies—70 to 80% of the effort might center around data cleansing. Some brands, like Williams-Sonoma, already have good data and are organized enough to begin working on more complex problems—such as whether or not to incent anonymous website visitors to sign in, or the way customer behavior insights can work with online ad buys.

“How do we tie together this core of very good and useful data, representing thirty years of transactions, with the very fleeting, ephemeral world of the ad exchange?” said Williams-Sonoma’s VP of Customer Analytics Mohan Namboodiri in describing a recent challenge.

Levi’s by contrast is further back in the process. “Our data is a mess, honestly,” Rafferty confessed. The company never anticipated its databases would be useful for future business decisions and customer insights until relatively recently. “As a result, we’ve merged a couple of databases and our team has had to spend a ton of time cleaning and validating the data,” he said.

For Levi’s, this means combining census data with store data and data from customers—pulling point-of-sale (POS) information in the hopes of gaining insights into behavioral and buying trends.

Apply analytics to improve the in-store experience

Certainly, CRM is a well-known application of in-store analytics. A loyalty plan or VIP customer buys an item, and a prompt at the register tells the checker to treat this individual differently.

Williams-Sonoma offers experiences—like cooking classes or free in-home design services—that appeal to its customer base. “There are some initiatives in emphasizing the local aspect of a store,” Namboodiri said. “Bringing in foods and practitioners who are specific to a store area is a differentiator.”

The next step is contacting the customer based on interests. Currently, Williams-Sonoma has outbound call lists based on discontinued collections. If a customer has shown interest in a collection in the past and the collection is about to be discontinued, a store associate can call the customer to inform her.

Williams-Sonoma is currently looking at how this can apply in-stores. “We’re not there in terms of instrumenting applications to let store associates approach customers and look them up right on the spot and introduce cross-sells or opportunities [immediately],” Namboodiri said. “But that’s not a far-off proposition.

And there are other, more subtle ways analytics can improve the in-store experience.

“Where we have [the] biggest opportunity for growth and the biggest challenge is assortment planning,” said J.Crew’s Hamburger. For J.Crew, in-store personalization means being able to know the shopper well enough to assemble the right products—and the right amount of products—based on local or seasonal considerations and online activity. This could mean, for instance, making sure certain products delivered to stores are tissue-wrapped to take advantage of a certain trend or buying habit.

Customer analytics can’t always be applied directly to the customer

Unlike J.Crew and Williams-Sonoma, Levi’s sells its products wholesale, meaning it’s one step removed from the consumer buying process. After all, a customer buying Levi’s jeans at Macy’s isn’t buying directly from Levi’s. How, then, can Levi’s apply customer analytics without that straight-through line to the customer?

The answer is to apply analytics to the retail partners where customers are purchasing. “One of our major customers, a retail chain, has two very different consumers shopping there,” Rafferty said. “How do you sort to the specific store? That’s where we find the power in applying analytics. Consumer shopping in [different] stores is different and we need to understand what the differences are and merchandise and market to them. Analytics plays a key role in terms of inventory.”

It was precisely this process that enabled Levi’s to identify the unexpected sales growth of 501 jeans among urban consumers. Analytics allowed Levi’s to tailor its marketing to the right demographic, and its inventory to the right outlets.

It also clued Levi’s in when the company got a little overzealous. “As we exploited [the finding], we got too far over and too diluted in what we defined as the urban consumer,” Rafferty said. Consequently, Levi’s pulled its messaging back to appeal to its core 501 market.

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