Big Data and the Demise of Analog Retail

The CEO of Best Buy has abruptly stepped down.

The CEO of Best Buy has abruptly stepped down. According to the Wall Street Journal he did do apparently because of his “personal conduct.” But the recently announced $1.7 billion quartely loss is still the news that matters most to the future of Best Buy and other “Big Box” retailers. And while the cost of operating brick-and-mortar stores as opposed to selling online is what seems to most as the culprit, I would argue that missing the potential of big data is–or will be–the great undoing of traditional retailers.

The Journal article quotes Craig Johnson of retail consultancy Customer Growth Partners: “Best Buy is a very dated store experience, rooted in the 1990s, and they need someone visionary.” Question is, what exactly is dated about the “dated store experience”? Johnson provides the numbers that most commentators focus on: Best Buy’s operating income per square foot was  $18.52 last year (down from $50.61 in 2006). By contrast, “Apple’s retail stores reaped an astronomical $4,700 per square foot last year.”

Indeed, Best Buy finds itself “stuck in the middle,” to use Michael Porter’s terms, between Apple’s product differentiation (both the design of the actual products sold and the design of its stores) and Amazon’s cost leadership. But maybe Porter’s terms are also somewhat dated. Maybe we are witnessing the rise of a completely new big data “generic strategy” which leaves Best Buy and other traditional retailers “stuck outside.” They are left outside of the big data analytics mainstream, stuck on the bank of the river of data that is generated by online sales, watching their online competitors generating not only less-costly sales transactions but also data–on transactions, locations, logistics, customers, potential customers–and knowledge that is used in a virtuous circle to generate more sales and increase customer loyalty.

A recent BusinessWeek article, “Why Wal-Mart is Worried About Amazon,” pointed out that the world’s largest retailer gets only 2% of its revenues from online sales. Same story with Target. There is no doubt that a big part of the challenge for traditional retailers is that more and more consumers are embracing online as opposed to analog retail, a trend that is accelerating because of the rapid proliferation of smart mobile devices.  But I think that an emerging difficulty for traditional retailers–and one that is very significant for their future–is that they are not experiencing and experimenting with big data.

They know it. According to the BusinessWeek article, Wal-Mart has developed an app that “scans the social media preferences of a consumer’s Facebook friends and suggests gift ideas sold on Walmart.com. To roll out more such innovations, Wal-Mart must improve its  in-house e-commerce technology, so [Jeremy King, formerly of eBay, and now chief technology officer, @WalmartLabs] will hire 87 engineers and coders to bolster the links between the stores and the website.”

Still, some retail experts argue that “knowing purchase patterns and behaviors is not the same as knowing people….  Lululemon, the hugely profitable and wildly successful purveyor of yoga wear, eschews ‘Big Data’ in favor of old fashioned techniques such as walking the store, talking to customers and eavesdropping on dressing room conversations to figure out what customers want… Costco could use its membership card to track customer purchases and distinguish between loyal and occasional shoppers. Instead Costco makes its membership card a profit center, ignores complex customer data analytics and focuses instead on having a unique customer experience built on great brands at great prices, clean wide aisles, well trained store associates, a cheap cafeteria and treasures buried in different aisles.”

But what if in five years the “clean wide aisles” have no shoppers? And what if they have no shoppers not so much because of cost disadvantages but because they have not used big data analytics to connect to and keep their customers?