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Jul. 21, 2008
Get to Know Joe: Predictive Analytics Can Create Utopia for Your Most Valuable Customers
By Michele Eggers, SAS
Imagine for a moment a world where your customers' experience interacting with your organization is truly exemplary. I mean a world where you really understand your customers: their needs, their cross-channel behaviors, their likes and dislikes. Let me illustrate with two customer experiences:
The illustrations are plentiful. We can all imagine an ideal world in which we make the most relevant, timely and profitable offers to our most valued customers to grow the relationship or keep them from taking their business elsewhere. Or one in which we, conversely, have the necessary insights to make the decision not to waive the fee or make that unprofitable offer to a low-value customer. And when you consider that 50 percent of an average bank's customers are unprofitable, that's a big problem.
Core enablers By gaining deeper customer insight, you have a better perspective on who your most valuable customers are, which ones are likely to respond to offers and which are at risk of attrition. Predictive analytics provide a superior edge for firms looking to know, not guess, what the right offer should be—or if an offer is appropriate at all. For example, by understanding a customer's current and potential value, you could flag individual customers or segments eligible to receive a waived fee or other special considerations. Once armed with customer insight, your company can better interact. That interaction must be across multiple channels and must provide an interactive environment that is agile to each unique customer experience. Your marketing technology must provide an outlet to input these real-time data points to determine what the right cross-sell offer should be—and if you should be making a cross-sell offer at all. Finally, your technology needs to help you to continually learn and improve from every customer interaction. Figure 1 illustrates how the customer utopia process technologically maps to these enablers.
A great example of this is a major financial services firm in the United States. Executives started by building a customer intelligence platform on which to base the organization's sales and marketing strategy. On that platform, the company performs an overall analysis of customers to segment, first on profitability, and then into sub-segments by credit risk, attrition risk and potential. Then, the firm uses the system as a cross-channel sales-and-marketing decision hub where daily decisions are made around actions such as deposit authorizations, proactive and reactive retention efforts, credit authorization, collection strategies and cross-sell offers. The integrated marketing platform triggers decentralized, yet relevant and profitable, decision-making across the organization to best serve the customer and the firm. And in doing this, the organization has seen its average customer value increase by 144 percent. The lesson to be learned is that consistent management of customer interactions across the enterprise will lead to customer-centricity, which in turn leads to greater customer profitability. I guess utopia isn't so inaccessible, after all!
Michele Eggers, a manager in SAS' Customer Intelligence Global Practice, has helped hundreds of marketers use technology to enhance customer relationships. She holds a bachelor's degree in finance from the University of Illinois at Champaign-Urbana and an MBA, with a concentration in marketing, from the University of Illinois at Chicago.
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