It’s hard to imagine an industry that knows more about their customers over time than companies that protect us and our assets against risk—yep, those folks that insure consumers and businesses. But while the insurance industry does a pretty good job bringing on new customers, it doesn’t do quite so well when it comes to targeting and selling more to the lucrative business they already have. Worse still is the fact that insurers often don’t know which customer segments generate the optimal “profit to risk” mix, meaning that that insurer may be hanging on to money-losing business (see also January 1 “Pricing Is The Sweet Spot”).

Given the knowledge they have of consumer lifestyles, why can’t insurers identify the ideal customer, and once that customer is on board, sell them more, higher-value services? Three hurdles get in the way of making customer insight actionable:

• Industry market structures produce fragmented data: Insurers are stuck with legacy systems required by regulators, or deliberately built to support distinct business processes or inherited through multiple acquisitions. These separate systems have isolated marketing and sales, leading consumers—like this analyst—to ask, “If the AARP knows I’m turning 50, why doesn’t my insurance company?”

• Hygiene wins over innovation: Insurance IT thought they succeeded if they didn’t cause customer loss, so what they measured was more about system performance. As a result, IT could provide lots of information about call center performance, but often little that the carrier’s marketing department could use for new product development.

• Historical IT spending leaves little for new thinking: Innovation and insurance don’t always go together. When it comes to the competition for IT dollars, the stuff that keeps the lights on, like application maintenance, always wins over the IT that supports the innovation and entrepreneurship that creates first mover advantage.

Good sales and marketing strategy begin with customer segmentation, and being able to put the customer base into meaningful segments, and then predict how these segments will behave demands technology. Forrester recently surveyed 83 insurers in North America to learn how each planned on deploying a key technology—predictive analytics—during 2009. We learned that when it comes to IT plans for 2009, insurers are in the “dabbling” stage, and more likely to say they were just checking out predictive analytics technology in 2009.

This 2009, consideration will translate into budget and spending for analytics solutions in 2010 and 2011, and the emergence of more insurance-specific solutions from the likes of broad analytics players such as IBM, SAS and SPSS as well as insurance specialists such as Eagle Eye Analytics and Valen. And, hopefully, more timely offers to existing policyholders ready and willing to buy more relevant coverage.

Ellen Carney is a senior analyst with Forrester Research. She focuses on how the financial services industry researches, procures and deploys business technology, and is responsible for developing the global forecasts for IT budget and spending forecasts for insurance and banking. She can be reached at

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