Increasing customer satisfaction has been found to lead to higher future profitability (Anderson, Fornell, and Lehmann 1994), lower costs related to defective goods and services (Anderson, Fornell, and Rust 1997), increased buyer willingness to pay price premiums, provide referrals, and use more of the product (Reichheld 1996; Anderson and Mittal 2000), and higher levels of customer retention and loyalty (Fornell 1992; Anderson and Sullivan 1993; Bolton 1998).
Increasing loyalty, in turn, has been found to lead to increases in future revenue (Fornell 1992; Anderson, Fornell, and Lehmann 1994) and reductions in the cost of future transactions (Reichheld 1996; Srivastava, Shervani, and Fahey 1998). All of this empirical evidence suggests that customer satisfaction is valuable from both a customer goodwill perspective and an organization’s financial perspective. A firm’s future profitability depends on satisfying customers in the present – retained customers should be viewed as revenue producing assets for the firm (Anderson and Sullivan 1993; Reichheld 1996; Anderson and Mittal 2000).
Empirical studies have found evidence thatimproved customer satisfaction need not entail higher costs, in fact, improved customer satisfaction may lower costs due to a reduction in defective goods, product re-work, etc. (Fornell 1992; Anderson, Fornell, and Rust 1997). However, the key to building long-term customer satisfaction and retention and reaping the benefits these efforts can offer is to focus on the development of high quality products and services.
Customer satisfaction and retention that are bought through price promotions, rebates, switching barriers, and other such means are unlikely to have the same long-run impact on profitability as when such attitudes and behaviors are won through superior products and services (Anderson and Mittal 2000). Thus, squeezing additional reliability out of a manufacturing or service delivery process may not increase perceived quality and customer satisfaction as much as tailoring goods and services to meet customer needs (Fornell, Johnson, Anderson, Cha, and Everitt 1996).
Measuring Customer Satisfaction While it seems clear that increasing customer satisfaction is beneficial to a marketing manager, how to measure it is less clear. Customer satisfaction has been studied from the perspective of the individual customer and what drives their satisfaction (Oliver and Swan 1989; Oliver 1993; Fournier and Mick 1999) as well as from an industry-wide perspective to compare customer satisfaction scores across firms and industries (Fornell 1992; Anderson, Fornell, and Lehmann 1994; Fornell et al. 996; Mittal and Kamakura 2001), while other research has examined customer satisfaction in a single organization (Schlesinger and Zornitsky 1991; Hallowell 1996; Loveman 1998) or across several organizations (DeWulf, Odekerken-Schroder, and Iacobucci 2001). In addition, specific tools for measuring customer satisfaction have been developed in thepast, including SERVQUAL (Parasuraman, Berry, and Zeithaml 1988, 1991). Thus, there exists an ample literature on which to draw when attempting to measure customer satisfaction.
In attempting to measure customer satisfaction, it is possible that attributes can have different satisfaction implications for different consumer and market segments – the usage context, segment population, and market environment can influence satisfaction and product use (Anderson and Mittal 2000). Failure to take into account segment-specific variation may lead a firm to focus on the wrong aspect for a given set of consumers (Anderson and Mittal 2000).
Furthermore, consumers with similar satisfaction ratings, yet different characteristics, may exhibit different levels of repurchase behavior (Mittal and Kamakura 2001). It is clear, then, that market and consumer segments should be important factors to consider when measuring customer satisfaction and its implications. Garbarino and Johnson (1999) did consider segments in the customer base in their study of satisfaction where they analyzed the different role played by satisfaction between low relational and high relational customers.
Their study, however, involved customers from only a single organization. Our approach extends this work by studying customers from multiple organizations, and shares some similarities with Anderson and Sullivan (1993) with respect to the type of analysis and sampling methods. The goals of their research, however, were to study the antecedents and consequences of customer satisfaction rather than investigate how different types of satisfaction may influence the overall measure of customer satisfaction.
In addition, our theoretical approach shares some similarities to Hutchison, Kamakura, and Lynch (2000) who posited that unobserved heterogeneity is a problem for interpreting results from behavioralexperiments. The basic point of their argument is that aggregation may create effects that do not exist in any segments, or may mask effects that do exist. The present study makes a similar point and provides an analytical method for overcoming such a problem.