Segmenting data optimally

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Kent Grayson is the Bernice and Leonard Lavin professor of marketing at the Kellogg School of Management at Northwestern University. BtoB asked Grayson about optimal segmentation in database marketing, his specialty. BtoB: Do you have any thoughts on how to segment optimally? Grayson: For some applications, Standard Industrial Classification (SIC) codes really do distinguish among customers and their needs, but it depends on what you're selling and your unique benefit. The problem with any pre-existing customer category like SIC codes is that it doesn't take into account customer needs. For example, some might think that health care companies and manufacturing companies are different when it comes to a particular automation or financial software, but actually their needs are the same. BtoB: What's your opinion of behavioral segmentation? Grayson: It's a relatively new aspect of segmentation that doesn't always see new stuff. The assumption here is that one data point can reveal quite a bit about a customer's needs. But I would say that you don't know what that signifies, to segment based on one piece of behavior. In b-to-b, there is less recreational website browsing, so you can make better assumptions about customer needs if, say, they downloaded a white paper. But b-to-b marketing also involves talking to your customer-facing people, such as customer services and sales, about what makes one customer different from another, before deciding on the dimensions that are important for segmentation. —C.H.
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