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Simplifying Web segmentation

Life stage segmentation—long an effective off-line technique—can be a powerful, cheap, and easy-to-use tool for mass-market B2Cs.

Mass-market business-to-consumer (B2C) companies may have the tools they need to gain knowledge about every aspect of their customers’ lives and thus to build personalized, profitable relationships with consumers. Unfortunately, acquiring the kind of information these tools need is a time-consuming and invasive process requiring customers to answer detailed questionnaires about their lives or to complete a lengthy series of transactions, and most of them just don’t stick around long enough to provide a clear picture of their identities, needs, and tastes. Fortunately, there is an easier way to segment B2C consumers. It has worked well for a long time in the off-line world and can help B2Cs increase their appeal to customers from the start.

Empirical research shows that it is content, above all, that lures consumers to any World Wide Web site and persuades them to return.1 To woo them successfully, a B2C—horizontal portal, mass marketer, and on-line community alike—must use tools that can anticipate customers’ future needs, even without a complete picture of their tastes and circumstances. Because the surfing public has a wide range of content preferences, mass-market B2Cs face the formidable challenge of developing superior content that appeals to a highly diverse population. (On-line niche players, by definition, have a better idea of their audience, though it is bound to be smaller.)

Pay-TV companies, which face similar problems, assemble a variety of programs or channels, often acquired from third parties, that together satisfy the interests and preferences of the audience. A recent McKinsey study found that pay-TV companies could best uncover those interests and preferences by using basic sociodemographic variables—age, employment status, family role, and household structure (Exhibit 1)—which provide a better indication of the broad content preferences of large groups of consumers than any combination of widely tracked factors such as occupation, income, and attitude toward technology.

Chart: What predicts content preferences?

B2C companies should find the four variables just as effective; indeed, B2Cs using them have sharply increased the percentage of Web site visitors who become customers—in the case of Ándale, the leading auction services provider for on-line sellers, by more than 100 percent in some channels. Even a subset of the variables (age, for instance) has proved useful to B2Cs such as the sporting-goods retailer Fogdog. The even better news is that segmenting customers in this way is comparatively easy: companies don’t need to invest in complicated data-mining software (similar segmentations have been used off-line for years), and other companies with on-line operations and specialists like DoubleClick can provide the necessary data. Since the information can be acquired without complicated customer databases or long registration forms, surfers get a personalized experience starting with their very first visit to the Web site.

Taken together, age, employment status, family role, and household structure, without further analysis, organize visitors into segments based on life stages (Exhibit 2). And if you know a consumer’s life stage, you already know quite a lot, since the content preferences of high-school teenagers, say, differ significantly from those of young mothers of small children. Creating appealingly differentiated content for each segment is a relatively simple task for B2Cs.

Chart: A simpler segmentation

Life stage segmentation is also likely to go on providing a B2C with guidance about its customers long after they have made their first visit to its Web site. Businesses tend to find their most profitable customers concentrated in certain life stage segments, which of course vary from business to business. Life stage segmentation allows a B2C to focus on improving its overall offer to its most valuable customer groups from the start. Moreover, the B2C will be able to work out a long-term strategy without having to develop lifetime-value and content-preference data for a large base of customers.

As target customers successively enter each new life stage, they demand a different kind of product. Although they will be moving into less profitable segments, serving them there will probably make better economic sense than incurring the cost of acquiring new customers in more profitable ones. Life stage segmentation makes it possible for B2Cs to anticipate the evolution of their customers’ needs—and thus to prepare their own growth path.

About the Authors

Eduardo Hütt is a principal and Robert Le Brun is an associate principal in McKinsey’s New Zealand office, and Thilo Mannhardt is a director in the Johannesburg office.

Notes

1Internet Portal Brands Survey, 2000, International Data Corporation.

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