The key to retail today is customer understanding —where each customer stands on his or her personal shopping journey, whether in-store or out. Retailers must “know” each shopper as never before. And they must offer the kinds of contextual, personally relevant experiences that will optimize their merchandise mix, create faster inventory turns, and drive greater customer engagement.
After all, the typical customer today is mobile, connected, and has heightened expectations. Many are accustomed to a deeper level of real-time interaction from innovative online retailers than from traditional brick-and-mortar stores.
Yet, as a recent Cisco study revealed, offline retailers – or retailers that combine on and offline capabilities – have their own unique advantages – if they step up to the opportunities of the Internet of Everything (IoE) economy. By blending the benefits of the physical store — such as the ability to touch, compare, and try on products — with the benefits of the virtual world, retailers can create a new value proposition that can’t be matched by their online-only competitors. In the process, they not only drive their own industry’s disruption but challenge for market leadership.
To do so requires them to have a core capability in analytics that will support the kinds of IoE-enabled experiences that customers will come to expect.
Online retailers already gain key insights from the rich data created by the “clickstream” as consumers browse, research, and purchase products online. Online retailers then use this data on likes, dislikes, and interests to gain a better understanding of each shopper’s journey. Offline retailers are bringing this clickstream into the physical world and gaining real-time insight into each shopping journey. In effect, clicks are meeting bricks.
But key to capturing unrealized value is “going to the edge.” Much of the IoE value for retail will be generated by innovations that depend on real-time analysis of data that is captured at the “edge” of the business — from sensors, RFID tags, IP cameras, access points, beacons, mobile devices, and even weight and motion sensors and ambient condition sensors for moisture and weather. The challenge is to turn this mountain of data at the outer boundaries of the retail network into relevant, real-time insights as close to the customer’s buying decision as possible
With a traditional model, it might take days or weeks to transmit all the data back to a central data repository, sort out what is relevant, and extract key insights. By that time, of course, the customer has left the store and the opportunity to close the sale is gone.
By analyzing data at the edge of the network, where it is generated, retailers can sort information in real time to address fleeting opportunities. They can use real-time insights to make contextual offers, reduce checkout times, ensure items are in stock, and optimize store operations. As our study confirms, consumers increasingly value and expect this level of personal shopping relevance.
With in-store sensors, wireless networks, and the right analytics solutions in place, retailers can gain a wealth of customer insight as they drive ever-greater efficiency, shopping engagement, and satisfaction. With a clear window into each shopper’s journey, the retailer can respond with agility to any situation, addressing customer needs in real time.
After all, the shopper in Aisle C who needs an automobile part for a fast fix requires a different experience than the shopper in the electronics department who is taking her time comparing prices in anticipation of a future TV purchase.
By leveraging analytics and building dynamic understanding of each shopper, a retailer can adapt to each customer’s needs in real time — and drive new levels of loyalty and engagement.
What do you think the future of shopping will look like based on the exploding amount of personal retail data? How do you envision your buying experience changing for the better through the use of real-time information available through retail analytics? I’d like to hear your thoughts on how analytics will redefine the meaning of a shopping trip as we know it.