Getting Closer to Customers

Just how real is the pressure retailers face to make sense of ever-growing mountains of data? IDC predicts that total data volume will reach 35,000 exabytes in 2020, compared with 1,200 exabytes last year. Ethnographer Elizabeth Lindsey dispenses with the numbers. “We live in a society bloated with data but starved for wisdom,” she says.

Data is bombarding retailers from every conceivable direction. Most of it is structured (think sales data, CRM and logistics), but the explosion of social media tools like Facebook and Twit-ter has created vast caches of unstructured data — everything from customer sentiment analysis to reviews, videos and images — that exist outside of retailers’ internal systems. The need to analyze and grasp the insights generated by both types of data — and to understand where the two intersect — is ushering in the next generation of business intelligence solutions.

In the last eight months there has been a flurry of new BI releases. While the bigger players look to push beyond the boundaries of an enterprise view, others excel in one or two core areas like mobile or social media.

For retailers, the goal is to use BI to provide more granular insight into inventory planning and execution, store operations and logistics, while at the same time gaining a more precise picture of customer behavior and buying patterns. A key trend cited by numerous retail experts is the emergence of real-time analytics — championed by the likes of SAS, Infor and FICO — that provides merchants with on-the-spot decision support. Real-time analytics has benefits that ripple across retail, from real-time inventory to real-time direct fulfillment and everything in between. The most compelling advantage: Getting closer to the customer.

Real-time wins
“R eal-time BI equals first mover advantage,” says David Dorf, senior director of technology strategy for Oracle Retail. “It’s simple as that. If a merchant sees a trend and is able to react to it before someone else does, they gain the upper hand. Retailers are now able to combine a data- and event-driven architecture with BI so that instead of receiving a report on Monday morning that says, ‘You need to look at that,’ they’re receiving an alert in real time when something is awry.”

This idea of linking BI with business processes, known as closed-loop analytics, enables retailers to detect, analyze, model and act as soon as something seems out of sync. So, for example, if a merchant receives an alert that an item is out of stock, it can instantly go to its dashboard and analyze why it happened. It can model responses by running “what if” scenarios and studying the effects of moving goods from one store to another. Once the merchant has reviewed all the data, it can quickly and efficiently execute a plan that is tied to the merchandising system and other business processes — allowing decisions to happen in hours, rather than days.

Leslie Hand, research director for IDC Retail Insights, points out that the shift to real-time decision-making is possible now because of vast improvements in technology infrastructure. “Ten years ago this level of computing power didn’t exist. Real-time was not within reach. Now we see retailers running toward BI because they realize the competitive advantage this provides — they know how critical it is to differentiate their business from competitors by connecting with consumers with personalized information and offers, while reducing their cost base,” Hand explains. “By leveraging BI across multiple business processes, retailers can deliver better service, make sure they have the right inventory, and be confident that stock levels are appropriate. Real-time BI moves the retailer closer to the consumer.”

Research compiled late last year through IDC’s Vertical Views survey suggests that retailers are ready to adopt next-generation BI tools. A survey of 210 retailers found that 48 percent are planning to invest in planning intelligence and 45 percent plan to invest in customer intelligence in the next 12 months.

Through the customer lens
Brian Kilcourse, managing partner with Retail Systems Research, insists that a big driver of investment in next-generation BI is what he calls the fourth dimension of data — the customer dimension. “Rather than looking at things just from a product-centric perspective, retailers are now looking at things from a customer-centric perspective,” he says. BI “allows them to look at localization schemes, integrated marketing efforts and numerous other processes alongside the customer dimension of data.”

Kilcourse also points to the role BI plays in what he dubs the “omni-channel imperative” that is forcing merchants “to take an enterprise view because they don’t know where the customer will start the dialogue. They have to be able to start the dialogue wherever the customer wants to start it — and these days there’s a good chance it won’t be in the store.”

The ability to connect consumer behavior across channels and leverage that data to develop a more detailed view of consumer buying patterns and preferences is identified by Patricia Waldron, worldwide retail analytics leader for IBM, as the most notable change in next-generation BI.

“Retailers are now able to look at their organizations through the lens of the customer … to get to know their customers at a deeper, more meaningful level,” she says. “They now know where the consumer shops, what she looks at, how the shopper likes to be marketed to and how best to communicate with that shopper.”

More powerful technology and better information allow retailers to “do a much better job of targeting consumers,” Waldron says. “In other words, if you’re a single person with a dog, you won’t be getting cat food coupons anymore.”