September 23, 2017

Data is the Key to Retail Evolution

By Matthew Tilley
Categories

Amazon’s recent move to acquire Whole Foods Inc., sparked yet another round of “is this the end of traditional retail?” stories. While it seems easy to buy into this narrative–judging from the rash of recent store closures among major retailers–the truth is that brick-and-mortar stores are not doomed to extinction, but rather we are witnessing the inevitable evolution of retail as a whole.

Most retailers understand that their ecommerce and physical storefronts aren’t mutually exclusive. In fact, successful retailers are developing a hybrid retail model as the best chance for long term success where physical stores can serve as branding and experiential showroom to buy online sales while ecommerce properties serve as efficient, convenient sales channels.

While this convergence has implications for the entire retail enterprise—from the P&L to marketing efforts and supply chain logistics—the first step is figuring out the right mix of ecommerce & brick-and-mortar suited to the retailer’s desired customer experience and brand image. There’s hardly a “one-size-fits-all” solution. The mix will vary by store type, brand and market.

How do retailers solve for the optimal mix?

The key is data. More specifically, data parity across all of their online and in-store properties. While the best retailers have the data and insights to understand what is working and what isn’t for their ecommerce sites, most don’t have that kind of view into their physical stores. Bringing this same level of insight into the physical store has been cumbersome and complex, leaving the brick-and-mortar side of the equation at a disadvantage. But without the offline perspective, online insights leave something less than a full view of the consumer.

Without the data, retailers will tend to swing between an in-store bias–retrofitting everything around the physical store because that’s their heritage—and an ecommerce bias–adding on the store experience as a physical showroom for their virtual online presence. The only way retailers can escape this bias pendulum is real data. But, in panels and presentations at a recent Future Stores event Seattle, most of the retailers pointed to customer feedback as their direction for what needs to change about their physical stores. And when asked how they evaluate the success or failure of changes or tweaks, at best they based it on a secondary metric, or at worst, a gut feeling.

To help retailers evaluate what needs to be enhanced or created in the physical environment, they need real, actionable data about what is happening in their stores. Not just post-purchase surveys or cameras that capture some of the action, or bias-prone “shop alongs,” but actual insights into how customers move through the physical space and what, if any, interaction that movement has with store sales, foot traffic, and other profit-producing behaviors.

The good news is that advanced offline consumer data analytics are available. In-store pathing and sensing technologies give retailers a comprehensive view of in- store activity. These solutions allow store operators to better understand the physical path-to-purchase, enabling them to organize stores based on what engages customers and what keeps them coming back. Out-of-store data captured at the household level, such as demographics, retailer spending history, product purchasing habits, online interests and purchase intent indicators give brick- and- mortar retailers the opportunity to know their local customers more intimately and tailor traffic driving campaigns to those specific interests.

While finding the optimal mix of online and brick- and- mortar presence may never be easy, it is achievable by practically every retailer if they embrace the data that’s available. Making the right technology investments can help them build resiliency to drastic shifts in the industry, and give them the intelligence and agility to ward off predators, thus ensuring their successful evolution into a new, enduring retail class.

Infographic-PathPoint-make-your-data-work-for-you

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