Our benchmark research into retail analytics says that only 34 percent of retail companies are satisfied with the process they currently use to create analytics. That’s a 10 percent lower satisfaction score than we found for all industries combined. The dissatisfaction is being driven by underperforming technology that cannot keep up with the dramatic changes that are occurring in the retail industry. Retail analytics lag those in the broader business world, with 71 percent still using spreadsheets as their primary analysis tool. This is significantly higher than other industries and shows the immaturity in the field of retail analytics.
While in the past retailers did not need to be on the cutting edge of analytics, dramatic changes occurring in retail are driving a new analytics imperative:
Manufacturers are forming direct relationships with consumers through communities and e-commerce. These relationships can extend into the store and influence buyers at the point of purchase. This “pull-through” strategy increases the power and brand equity of the supplier while decreasing the position strength of the retailer. This dynamic is evidenced by JC Penney, which positions itself as a storefront for an entire portfolio of supplier brands. Whereas before the retailer owned the relationship with the consumer, the relationship is now shared between the retailer and its suppliers.
What this means for retail analytics: Our benchmark research shows retail has lagged behind other businesses with respect to analytics. Given the new co-opitition environment with suppliers, retailers must use analytics to compete. Their decreasing brand equity means that they need analytics not just for brand strategy and planning, but also in tactical areas such as merchandising and promotional management. At the same time, retailers are working with ever-increasing amounts of data that is often shared throughout the supply chain to build business cases and to enrich customer experience, and that data is ripe for analysis in service to business goals.
E-commerce is driving a convergence of offline and online retail consumer behavior, forcing change to a historically inert retail analytics culture. As we’ve all heard by now, online retailers such as Amazon threaten the business models of showroom retailers. Some old-line companies are dealing with the change by taking an “if you can’t beat ’em, join ’em” approach. Traditional brick-and-mortar company Walgreens, for instance, acquired Drugstore.com and put kiosks in its stores to let customers order out-of-stock items immediately at the same price. However, online retailers, instead of looking to move into a brick-and-mortar environment, are driving their business model back into the data center and forward onto mobile devices. Amazon, for instance, offers Amazon Web Services and Kindle tablet.
What this means for retail analytics: There has historically been a wall between the .com area of a company and the rest of the organization. Companies did mystery shopping to do price checks in physical trade areas and bots to do the same thing over the Internet. Now companies such as Sears are investing heavily to gain full digital transparency into the supply chain so that they can change pricing on the fly – that is, it may choose to undercut a competitor on a specific SKU, then when its system finds a lack of inventory among competitors for the item, it can automatically increase its price and its margin. Eventually the entire industry, including midtier retailers, will have to focus on how analytics can improve their business.
Retailers are moving the focus of their strategy away from customer acquisition and toward customer retention. We see this change of focus both on the brick-and-mortar side, where loyalty card programs are becoming ubiquitous, and online via key technology enablers such as Google, whose I/O 2012 conference focused on the shift from online customer acquisition to online customer retention.
What this means for retail analytics: As data proliferates, businesses gain the ability to look more closely at how individuals contribute to a company’s revenue and profit. Traditional RFM and attribution approaches are becoming more precise as we move away from aggregate models and begin to look at particular consumer behavior. Analytics can help pinpoint changes in behavior that matter, and more importantly, indicate what organizations can do to retain desired customers or expand share-of-wallet. In addition, software to improve the customer experience within the context of a site visit is becoming more important. This sort of analytics, which might be called a type of online ethnography, is a powerful tool for improving the customer experience and increasing the stickiness of a retailer’s site.
In sum, our research on retail analytics shows that outdated technological and analytical approaches still dominate the retail industry. At the same time, changes in the industry are forcing companies to rethink their strategies, and many companies are addressing these challenges by leveraging analytics to attract and retain the most valued customers. For large firms, the stakes are extremely high, and the decisions around how to implement this strategy can determine not just profitability but potentially their future existence. Retail organizations need to consider investments into new approaches for getting access to analytics. For example, analytics provided via cloud computing and software as a service are becoming more pervasive help ensure they meet the capabilities and needs of business roles. Such approaches are a step function above the excel based environments that many retailers are living in today.