Knowing the Customer

Most companies engaged in the retail sale of services or products know a great deal about who their customers are through the analysis of demographic data. Demographic data include a customer’s age, gender, estimated income, and area of residence, among many other things. These are descriptive facts that marketers use to segment customers with the goal of better tailoring marketing messages and product attributes. Some age-based (generational) segments are well known: baby boomers, yuppies, GenX’ers, and slackers among them. Actually, those labels imply more than age. They imply something about personal values and lifestyles, and that is where psychographics comes into play.

Psychographics is the practice of learning about the personal values, interests, and activities of current and would-be buyers to further segment customers into finely tuned groups for even more specific product or message tailoring. Relevant psychographic data typically come from surveys and focus groups. Those data are combined with demographic data to create profiles of like-minded customers. The profiles typically define nonoverlapping “types” of buyers and potential buyers. Differences between those types become the basis for specifying marketing tactics, product or service attributes, service levels, and so on.

Many sources of data can be used to conduct demographic and psychographic analyses. Some of those data, particularly demographic data, are publicly available; one example is census data. Psychographic data are more likely to be the proprietary property of marketing services firms or opinion polling companies and are sold to interested parties. Some data, however, are the unique province of a single company. Specifically, companies that provide goods and services have facts about their customers that no one else can know. Important details about customer behavior reside in such data, including how much customers spent on the most recent transaction, their spending patterns over time, and their loyalty. Taking advantage of this data has been central to the process of knowing the customer.

Discerning important facts about customer behavior is invaluable. For example, at one time it generally was believed that a firm’s market share is positively related to its profitability. Data analyses have shown that this is not always the case. Building market share entails customer acquisition costs that, depending on the company and industry, may undermine profits for many years. Others believe that customer loyalty matters more than market share, as Frederick Reichheld postulates in The Loyalty Effect.^[1] Loyal customers do hold down acquisition costs, but loyalty may pay off in other ways: by increases in spending as customers’ incomes rise with age, by referring new customers, and so forth. Further, certain current customers may be more profitable than others because they spend more, require little support, and pay their bills on time. A company with a small market share but with these types of customers could be far more profitable than a market leader with a less desirable clientele. Indeed, a great deal of customer behavior analysis today focuses on identifying a company’s most profitable customers.

“Knowing the customer” is essential for successful marketing and product or service specification. It is also essential in creating the human capital system that is best able to serve those customers. Different workforce attributes and management practices, for example, may be required to serve different customer segments effectively. We turn now to the linkages between customer outcomes and human capital management systems.

^[1]Frederick Reichheld, The Loyalty Effect. Boston: Harvard Business School Press, 1996.