This blog is part of series exploring the nature of customer-centricity. Read the preceding blog.

It’s a generalization, but I think few insurance people would regard themselves as marketers. They would probably tend to see themselves as risk assessors and mitigators, skilled creators of products to help customers protect themselves against life’s little knocks. But if I’m right, they are increasingly being asked to do this in a much more nuanced way, to fit the services they offer more and more exactly into their customers’ lifestyles.

In other words, they have to start thinking much more like marketers and, crucially, develop the marketer’s ability to build up a detailed picture of his or her customers and their behaviors and secret wishes.

This shift in focus for insurers comes at an exciting time, when new developments in analytics and artificial intelligence are transforming (and greatly improving) the key process in all this: customer segmentation. Traditional segmentation techniques involve identifying certain customer attributes that will be markers for a customer segment. Let’s say an insurer has 50 customer attributes captured: it needs to identify the six that will define a group of customers in whom it is worth investing.

But how do you know you’ve chosen the right six attributes? It’s like playing the lottery, with a 15 million-to-one chance! Things are more challenging since the advent of big data because the total number of customer attributes available is much larger. Even if the number of attributes doubled, one would have more than 1 billion options.

There are many other complexities but I think you get my point: trying to use reason and/ or intuition to produce relevant customer segmentation is, at best, a very partial solution focused on a single dimension of customer attributes. Such segmentations are soon outdated.

New approaches use artificial intelligence to take an infinite number of attributes into account and to align the resulting solution with business objectives. These next-generation approaches are dynamic, allowing the segmentation strategy to address who to focus on, what to offer and what to say, and where to find them—all while balancing customer dimensions and business objectives.

This rigorous segmentation approach is the foundation of a more personalized brand experience, which is exactly what Generation D wants. For the insurer, it offers a way to link what marketing is doing with the company’s revenue targets and business strategy.

Of course, this type of technology and intellectual capital is in very short supply. Accenture has made it a focus to create a real capability in this area, and we have made some notable acquisitions to do so—we see it as something our clients in all industries will really need as they become digital insurers, bankers, retailers, manufacturers and so on. I think you’ll find these capabilities, which are branded Accenture Interactive, rather impressive.

For more on customer segmentation in general, read Winning the lotto: A fresh look at customer segmentation. And for a look at some research on the state of analytics in insurance—and some advice on how to get started—try Achieving payback in analytics insurance. An interesting look at how segmentation—and a rethink of their business models—will be key to insurers’ efforts to take advantage of the pensions crisis may be found in Consumers see the light as retirement shortfall looms.

Submit a Comment

Your email address will not be published. Required fields are marked *