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Getting Closer to Customers

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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.”

Playbook, please
W  ith more intelligence at their fingertips and sophisticated data tools in their arsenal, retailers are looking for solutions that help them to dig through the data and solve problems quickly. Kevin Sterneckert, research director for Gartner, reports growing interest in having a playbook. “Retailers will say, ‘I have this great BI tool that gives me all kinds of information and allows me to do pivot tables and read reviews and on and on, but how do I know where to look for my problem? And once I’ve identified the problem, how do I solve it?’”

Sterneckert reports that a handful of companies have come to retailers’ rescue by creating playbooks that “identify exception conditions and outline the steps to take to solve particular problems or go after specific opportunities.” Retailers also rely on advanced visualization tools and dashboards to discover actionable information. Dorf points out that the difference between first-generation dashboards and what’s being used now is improved ease of use, greater visual appeal and — most importantly — the ability to reduce the time to insight.

“The tools are built in such a way that the user doesn’t need to run multiple queries,” he says. “Data visualization allows someone to point to a slice of the pie and automatically drill deeper into the data.” Dorf also notes dashboards “are now role-based — merchants want their stuff, store managers want to get at different pieces of information. In some instances the data is very minute, but because front-end visualization engines have become so powerful that they want it delivered on mobile devices like smartphones or tablets.”

Taking stock
R etailers are also taking stock of their BI strategies as they relate to their mobile and social programs. The consensus among industry watchers and BI vendors is that a better understanding of the mobile customer and of how shoppers are using social media can be achieved by next-generation BI tools. Questions arise about which devices retailers will support and what their strategies will be, but all agree that mobile BI is an important component of enterprise-wide BI.

“The unbelievable pace at which we’ve seen shoppers adopt smartphones, coupled with the use of mobile tablet devices in retail stores, makes mobile BI a must,” Kilcourse says. “It will be important for retailers to know if the customer accessed a website via a mobile device. They may want to know where the shopper was at the time — were they in the store or at home, or maybe on the road.

“Mobile is a great opportunity to operationalize BI within the walls of the store,” he says. “If retailers can get the right information to the customer when she’s inside a store, the potential exists to influence demand. If an employee is using a mobile device, the opportunity is there to influence behavior.”

Sterneckert is also a champion of mobile BI. Gartner research indicates that traditional retailers will derive an average of 16 percent of total revenue from channels other than bricks-and-mortar stores by 2014. “In that context, having a better understanding of the mobile customer and how they interact with other channels is imperative.”

Understanding social networking’s influence on retail is another area of tremendous opportunity. Facebook alone has millions of users who routinely discuss companies and brands, trends and shopping experiences. Tapping into these new data sources — and finding the best ways to respond to the insights gained from this data — is considered the “next big thing” in BI. The challenge, as nearly everyone connected to BI acknowledges, is that this data is unstructured.

In the past year, several BI heavyweights have partnered with other vendors in an effort to tap this vast resource: Oracle engaged with Buzzient, and acquired Radian6, to name just a few. The plan is to gain a better understanding of the conversations that are taking place, discern whether they’re positive or negative, and attempt to determine relationships between changes a retailer may be making to its business and the reaction it is generating among shoppers.

“Success at mining the data from social media websites gives retailers the opportunity to understand pre-demand signals,” Kilcourse says. “Depending on how savvy a retailer is about using social networking tools, they can tell if they’re making the right moves or they can engage the consumer in a dialogue that leads to better decision-making.”

Sterneckert is equally excited about the prospects for social BI. “The ability to engage that customer and understand the trends that are bubbling up is quickly becoming a vital aspect of retailers’ go-forward strategy and a must-have in the BI basket,” he says.