VideoSuch stories have not exactly burnished the reputation of CRM software vendors. Nevertheless, the promise of analytics — better selling through science — appears to be gaining converts. Indeed, some companies are already engaged in predictive modeling and segmenting.
With predictive modeling, companies attempt to forecast future customer behavior based on analytic models. Segmenting, on the other hand, involves grouping customers by common traits or behavior patterns; clustering is one common analytic technique to help achieve this. Generally, businesses segment customers into groups to help them devise the most cost-effective way to market and to service those groups.
Segmenting is not limited to existing customers, however. At Irvine, California-based Volvo Cars of North America, Phil Bienert, manager of the automaker's CRM & E-business group, says his department is currently in the middle of a segmentation project involving prospective customers. According to Bienert, Volvo is breaking current customers into segments, and then comparing the patterns of those groups with those of prospective buyers. The patterns can be obvious — customers moving up the auto food chain, for example, from compacts to midsize cars to SUVs — or hidden, the kind that companies need analytics to uncover.
The goal is to identify behavior that indicates a propensity for buying a Volvo down the road. "You can apply these owner characteristics to hand-raisers [those who request information about Volvo products] and cluster them," explains Bienert. "Then you can prequalify people who haven't even entered into communications with the company." (Like many large companies, Volvo buys consumer data from third parties.)
Should You Dump Customers?
Of course, not all hand-raisers will prove to be valuable customers. Indeed, some executives argue that not all customers are valuable customers. At electronic and industrial communications products maker Woodhead Industries Inc., CFO and vice president of finance Robert Fisher says management's thinking in the past has been that any customer is a good one. "We'll sign up anybody who will sell our products," he says. "That may not be so smart."
To get a little smarter, Woodhead (also based in Deerfield, Illinois) has started developing a framework for lead management and contact information to work with global customers like DaimlerChrysler and Ford Motor Co. The company is also implementing a business-intelligence platform from PeopleSoft. Fisher says the technology will enable Woodhead management to see instantaneously what the company is shipping, by customer, product line, location, and the like. Further, sales managers will be able to group customers by gross margins. Says Fisher, "I want to identify customers who I want to spend more time with and the ones I want to dump."
He's not alone. Ditching costly customers has become something of a corporate mantra in the past few years. But some consultants say relying on clustering to deep-six a segment of customers can be a tricky business. In fact, some rail against the practice. "Rarely is it a good idea to dump a customer," insists Laura Preslan, research director at AMR. "The cost of acquiring a new one is so high."
What's more, profit profiles (which are usually based on overhead and other support costs) can be way off. Warns Gareth Herschel, research director at research firm Gartner: "You may end up kissing off an entire segment of valuable customers simply because you misfigured the depreciation of a printer in Poughkeepsie."
Analysts also point out that today's costly customer could turn out to be tomorrow's cash cow. Herschel recalls how, during the early 1990s, many companies were eager to ditch customers that placed a lot of calls to customer-service centers. But then the Internet came along, making it cheaper to service those customers and providing a lot of low-cost cross-sell and up-sell opportunities. "You were desperate to get rid of a customer," he says. "Now, you're not."
In other words, customers and their circumstances change. That's why analyzing customer information remains an imperfect — and never-ending — quest. A case in point: a director of analytics at an Internet service provider (ISP) points out that users with the highest risk of canceling their service used to be those who simply didn't find the Internet interesting. Based on that data, the ISP might have considered launching such things as streaming video and music. Over time, however, the profile of likely defectors has changed. Nowadays, the customers most likely to break their service contracts are those who have slow-processing computers. Launching more entertainment features — those that require fast processors and tons of bandwidth — will do little to ease their pain.
For CFOs, the lesson is clear. Analytics tools are just that — tools, not cure-alls. "[Things] don't change simply because you open a box and pull software out," says Sunstar Butler's McMahon. "You're still the same company."
John Goff is technology editor of CFO.
Getting to Know You
Managers at Brother International, the U.S. subsidiary of Nagoya, Japan-based Brother Industries Ltd., are taking a fairly simple approach to analytics. Three years ago, the company, which sells its lines of multifunction centers, fax machines, printers, labeling systems, and sewing machines through office superstores and value-added resellers, decided it needed to do a better job of connecting with end customers. The plan: make better use of the 1.8 million telephone inquiries Brother receives at its customer call centers each year. In years past, much of that information simply scattered in the wind. "We didn't have the right tools," recalls Dennis Upton, Brother's chief information officer. "If a customer called us with a malfunction on a fax machine, we didn't know them from Adam."
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