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Can Analytics Save Brick and Mortar Retail?

Enterprise Software | Posted on May 18, 2018 by Arnab Chakravarty

There’s a doomsday scenario you often hear during discussions about how advanced analytics and other new technologies will affect the retail economy. It’s the “machines will take all our jobs” story. In this pessimistic forecast, we live in a society where traditional retail has all but disappeared. Algorithms recommend products to us, we order them with our phones, and we don’t ever see a human. As a consequence, entry-level service jobs disappear. The only non-technical jobs left are those in the warehouse and at the corporate offices.

But this scenario disintegrates once you think about it for a few moments. It depends on the assumption that brick and mortar is all about sales. This isn’t true. Customers go to retail to touch and even smell the product. In the case of luxury shopping, they go to see and be seen by other members of the social elite. Mall shopping is a recreational activity. As well, millennials love to Instagram, so compelling retail spaces create their own advertisement over social media. This certainly contributes to the fact that, according to the US Census, 90% of American purchases were made offline in 2017.

Accordingly, rather than assume that brick and mortar is dead, it’s more sensible to imagine that the presence of new technology will change or enhance it. And this appears to be what’s happening. Companies like Amazon and Tesla, rather than shying away from retail, are excelling at it. Let’s examine how they’re doing it, and what lessons retailers can extract from their methods.

 Amazon Evolves in Reverse

            It’s somewhat ironic that Amazon is getting into retail stores with Amazon Books. After all, they’re the primary challenge to old-fashioned literary retail. But now they’re entering the field themselves. Why?

Part of it is that they can do it better. By using advanced analytics on their vast corpus of data, they can perfectly tailor the stock of each store, only including the books they know that local customers want. We all know the feeling of wandering through a bookstore, trying to find even a single title that interests us. Amazon Books is in a unique position to banish that malaise from the retail experience.

But, more importantly, Amazon Books puts a new spin on the Amazon brand. The company has gotten a lot of bad press recently—including, but not exclusive to, stories about its fulfillment centers. This reporting, accurate or not, gives the impression of a faceless, unfeeling corporation. Amazon Books turns that around by dispensing books with smiling faces as well as the classic Amazon efficiency.

It’s a feedback loop, where online shopping analytics inform in-person retail, which then provides the human touch that’s lacking online.

Why You Can’t Drive Away in a Tesla

             Tesla isn’t like other car companies. It’s a manufacturer, but it’s also a retailer if an unconventional one. Rather than placing their cars in dealerships, Tesla has its own showrooms. But you can’t actually buy a Tesla on-premises—you can’t just drive one off the lot. So, why do they exist?

Well, in a way, removing the sales element actually makes for better retail. We’re all familiar with the caricature of the aggressive car salesman. That caricature happens to be true—car dealers have to hustle to make a profit. By contrast, when you walk into a Tesla dealership, all you receive is education and personal attention. It doesn’t matter whether you don’t want to buy a Tesla. It doesn’t even matter whether you’ll ever be able to. You get a hands-on experience with an exciting product and people who are passionate about it.

And, again, a feedback loop forms. In-store staff hears typical customer concerns about the Tesla brand. That information can then circulate to other sales teams (or, rather non-sales teams). The non-competitive structure of the dealerships makes for better knowledge of the customer. This powers online sales.

Also, Tesla is a prime example of a company that uses consumer data down the line, after the product is purchased. Just before Hurricane Irma hit, Tesla immediately extended a free power capacity upgrade to those who needed to evacuate, using GPS to find affected customers. While this specific offer is a thing that only Tesla can do, it should also inspire thinking about what retailers can do with customer data after they’ve left the store. Let’s say the weather forecasts are calling for a week of rainstorms. Why not send your most loyal customers an umbrella?

Over-the-Counter Analytics at Walgreen’s

             Walgreen’s is a huge, geographically dispersed retail chain. Among other things, this translates into massive burdens for an IT team, wherein a small number of experts have to travel from store to store, solving problem after problem. A dynamic like this punishes expansion. Each new store is a node in an annoying network.

This problem turned out to be a prime application for machine learning. By applying advanced analytics, Walgreen’s turned the situation around. Equipped with smart forecasting, their IT teams could batch jobs together and apply preventative maintenance. Instead of running around in panic mode all the time, they started nipping problems in the bud before they become crises.

This is a case of completely traditional retail being unshackled by analytics. Freed from drudgery, Walgreen’s IT staff can now pursue longer-term visions and higher-value projects.


In different ways, Tesla, Walgreen’s, and Amazon all demonstrate the various ways forward in a changing retail economy. Amazon provides an example of how personalization and physical space can reshape a brand while maintaining its competitive advantage. Walgreen’s shows how the application of analytics, with no change in the overall structure of an organization, can free up dormant labor. And Tesla shows that the role of retail can be completely re-imagined. The overall message is clear: online and brick and mortar aren’t locked in some kind of combat, or, at least, they don’t need to be. Instead, with analytics and some careful thinking, they can be an ecosystem that’s stronger together.

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