Too many ceo’s skipped English Lit on the way to an M.B.A. and now find themselves in the midst of their own morality play.
Like Christopher Marlowe’s Doctor Faustus—whose desire for complete knowledge led him to cut a deal with the devil and lose his soul—retailers have developed an unquenchable thirst for data.
And now they’re drowning in the stuff.
It’s not enough to know if you’re a store for soccer moms or socialites. Merchants today know the intimate details of their customers’ lives, from where they’re clicking before they buy online, to how they walk the store, to what they post on Facebook afterward.
There’s value in that knowledge to be sure—but it’s not an end in and of itself. Shoppers want to put together knock-your-socks-off looks. And for that, they need exceptional product and merchants willing to stock it—two key elements that many see lacking in the industry today.
Take the lament of Leonard Lauder, chairman emeritus of Estée Lauder Cos. Inc., who sees a U.S. department store industry that has grown “boring” as consolidation cut down on competition.
“No one is banging on your door, saying, ‘Give us something new for us to compete more effectively with,’” he recently told WWD. “The death of innovation is when finance trumps creativity. The reverse of it is when you’re dealing with a merchant who loves new ideas—say, Neiman Marcus or Saks Fifth Avenue or Nordstrom. They say, ‘Oh, what a terrific idea—when can we have it?’”
The industry hasn’t always oozed mediocrity.
Glen Senk, former chief executive officer at David Yurman and Urban Outfitters Inc. and now an investor, recalls an earlier time, when he worked with Bloomingdale’s Marvin Traub.
“Retail was theater,” says Senk, who is ceo of Front Row Partners. “It was transportive and I think a lot of people have forgotten that. [As a retailer] I always allocated some percentage of budget to funny money, to dreaming money, and I learned that in part from the way Bloomingdale’s was run.”
Senk recalls Bloomingdale’s “paradox department,” a buyer who was solely accountable for bringing in newness and surprise—forget the budget and markdown money.
In a similar spirit, Steve Jobs famously asserted that it wasn’t the consumers’ job to know what they wanted, but his job to create it.
The iPhone 6 is the only real contender for the crown of “must-have item” heading into the holiday season. Short of a big price cut, nothing else seems able to rouse the animal instincts of shoppers.
“Really great businesses are a combination of gut and instinct and art and creativity, and they’re balanced with analytics,” Senk says. “If you look in the rearview mirror more than seven seconds, you get in a car accident. Analysis tells you what happened in the past, it doesn’t tell you what’s going to happen in the future.”
And just because something is being measured, it doesn’t mean its importance has been weighed. Senk says consumer data does not always lead retailers to the right conclusion.
“They may say that such and such didn’t sell because it was pink, when it was an ugly pink,” he says. “That’s the difference between a merchant, which we have fewer of today, and a bean counter.”
But data on shoppers is literally coursing through the air today, with cell phones pinging beacons in stores and every “like” and “friend” recorded, stashed away and bundled for later use.
Information is not useless—it just doesn’t work in a vacuum. It needs to be put into the context of strong merchandising.
Fashion businesses need to learn how to nurture the designer’s creativity and take advantage of the consumer insights hidden in the nameless gigabytes.
That balancing act will be individual to every company, but no one’s going to get there without a keen understanding of how to make sense of the data and just what its limits are.
“Data is everywhere and it’s available to everybody—and the cost of capturing it is not that great anymore because of memory and computational power,” says Greg Petro, ceo of First Insight, which helps retailers more effectively set prices. “The insights that come out of the data are…interesting and rare.”
For example: After pouring through some 30 million data points, First Insight found that 11 percent of the products carried by retailers could carry a higher price.
“Designers are artists and creators of products, that is absolutely necessary,” Petro said. “We don’t believe the consumers can cocreate product. What we do believe is that [consumer data] can help you commercialize those products.”
Being able to squeeze the most out of the finite number of sales racks is a good thing. And getting into a trend online before it peaks and getting out before it collapses can mean more than a percentage point of margin here or a few more sales dollars there.
There’s real money to be had in becoming more effective at delivering more product at full price.
Katie Smith, senior fashion and retail market analyst at data company Editd, sits atop what she described as “the world’s largest apparel warehouse of data” with information on five million products being sold online.
“We know exactly what’s selling and at what price,” Smith says. (The company does this by dispatching “spiders” that poll retailers’ Web sites and track when a new style is posted, when its price is cut, when it’s taken off the site and so on).
Recently, Editd found that Forever 21 had 13,444 pieces online, with prices that ranged from 99 cents to $89.90 and an average of $14.66. Within that, the fast-fashion retailer had 115 styles of jeans in the $20 to $40 price range. That compared with 169 styles at H&M, or just 17 at Nasty Gal or four at Top Shop.
Information like that can help retailers, for instance, know when competitors are cutting price, indicating that the market for a particular look has become saturated.
ASOS has 200 people using Editd on a daily basis.
“It’s a way to identify market trends easily,” Smith says. “I would hope that would free up budget, time, energy for [fashion companies] to work on product that defines them. A computer isn’t going to replace this whole thing—it gives freedom, even though it’s a piece of software, it creates freedom.”
So far, retailers are getting only middling marks when it comes to their use of data.
Suketu Gandhi, a partner in the strategic IT practice of A.T. Kearney, describes retailers as “lemmings” that are “probably not” using data well.
To get the most out of data, Gandhi says retailers have to separate signals from the noise, distinguish between short- and long-term signals, know what will impact the revenue side of the equation and what will help with costs.
Knowing what questions to ask becomes very important.
“If you’ve got more than four questions, it’s too many—but if it’s less than two, it’s too few,” Gandhi says. “When you’re looking from the inside out, they tend to focus on delivery-cost questions. When you’re focusing the other way, which is customer-back-in, you tend to focus much more on revenue.”
He suggests trying to answer three questions that touch on revenue and one on how goods should be delivered.
The mass of information needs to be winnowed down somehow.
“Human beings cannot make decisions on this amount of data,” Gandhi says. “In merchandising, this is a very pernicious problem. Because they can’t find the next hit or the next ‘it,’ they say it must be in the data out there.”
There are companies that are widely seen as smart in their use of data, but they’re the digital giants, such as Google and, in e-commerce, Amazon.com.
Even though using data should be familiar to retailers, who have been dissecting sales information from the cash registers for decades, more parts of the organization have become engaged. The merchants use data to analyze competitors, the marketers use it to target customers and the top brass uses it to allocate dollars.
That has everyone pointing to some bit of data to justify themselves.
It’s made for something of an ever-escalating arms race. Consultant Amy ter Haar, who advises companies on personal data and privacy, says retailers are facing a new breed of consumer who’s always connected and sometimes has more information on product than retailers do.
“So being customer-centric is how they differentiate themselves,” she says. “They’re trying not to focus on the product side because they’re really trying to focus on the engagement—because they can’t really manage or shape the experience, because the customers are doing that themselves.”
To illustrate the risk of data overload, ter Haar turned to a sentiment from Mark Twain.
“Like a drunk using a lamppost, they use it for support more than illumination,” she said. “The same thing is happening with big data.”