Distinctions Between

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academic instruction, and entertainment industries. Many firms .... IO). (A comparison of attribute importance for newly acquired and loyal customers is shown in.
Distinctions Between

Photo by Harry Bartlett/FPG international

26 Spring 2000

New and loyal Customers

Marketing researcherS|Can gain useful insights by computing and comparing attribute impnrtanne

• Companies Com[ use satisfaction surveys strategically to determine importance. By doing so, they try to improve pertormance on those attributes that have the highest impact on overall satisfaction, and therefore on customer retention. To establish attribute importance, firms collect data from a single cross section of consumers. Then they use regression analysis, which assumes that attribute weights determined over a single cross section will generalize to the entire consumption experience. But what if this assumption is false, and attribute importance is dynamic?

By Vikas Mittal and Jerome M. Katrichis aik'ling research

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E X E C U T I V E

S U M M A R Y

A key aim of analyzing satisfaction studies typically is to estimate attribute importance; i.e., how changing performance on an attribute will affect overall satisfaction. And many analysts assume that the same attributes are important for all customers. The authors argue instead that the attributes important to newly acquired customers might not be the ones that are important to loyal customers. The authors present a simple methodology for computing and comparing attribute importance using data from the credit card, mutual fund, and automotive industries. A critical aspect of the methodology is post hoc qualitative research to gain insights into why attribute importance changes over time. It stands to logic, and many research studies show, that an attribute's importance changes as the customer's relationship with a product or service matures. Attributes that are important to newly acquired customers might not be the same ones that are important to loya! customers. Once firms realize that attribute importance is dynamic, they need to reconsider how satisfaction surveys are done, how the data are analyzed, and how the results are implemented. We present three cases in which firms addressed dynamic attribute importance in the context of their satisfaction studies. Specifically, these firms employed the Dynamic Attribute Importance Model (DAIM) as a blueprint for analysis and action, which enabled managers to determine changes in attribute importance as their customers' relationship with their product or service matured- An important aspect of the model is the use of qualitative research to understand the logic behind such shifts. Insights from quantitative analysis and qualitative research then were combined to create actionable blueprints for managing customer relationships. In this methodology, the statistical analysis Is used to uncover shifts in attribute importance, and the qualitative research is used to understand the reasons for such shifts. Uncovering the "why" behind shifts in attribute importance enables firms to better understand the dynamics of customer relationships. IMPLICATIONS OF DAIM Many managers understand that their firm can't be everything to all its customers. We suggest that a firm cannot be everything to all its customers, all of the time. With the increasing emphasis on long-term customer relationships and longconsumption cycles, managers must understand how consumer needs change. They can do this by understanding how the importance of an attribute changes over time. As the case studies show, attribute importance between newly acquired and loyal customers can vary drastically. Understanding the dynamic nature of attribute importance can help firms develop separate strategies for customer acquisition and customer retention. Often, the attributes that enable a firm to acquire a customer differ from those that help the firm 28 Spring 2000

retain the same customer. Moreover, the needs of newly acquired customers and loyal customers may vary substantially. As one executive remarked, "When customers graduate from a new to a loyal customer, we cannot continue treating them the same." We document differences in attribute importance between newly acquired and loyal customers for the automotive, credit card and financial services industries, although similarities also be can found for the telecommunications, health care, insurance, academic instruction, and entertainment industries. Many firms now combine their segmentation and satisfaction research. The idea is to see if attribute importance varies among different segments. DAIM suggests that customer duration should be used as a segmentation variable. Customer duration is a behavioral variable that is strategically important for firms because it affects profitability. By separating new and loyal customers, a firm can assess these customers' unique needs and tailor its satisfaction management strategy accordingly. This application is particulariy useful for services in health care, telecommunications, and financial services (banking, insurance, and mutual funds), for which the cost of acquiring a customer is relatively high, but the customer s likelihood to stay might not be so high because of intense competition. Many firms in these industries will attract customers based on economic rewards, but fail to retain them because the key drivers of their satisfaction might not be the economic rewards offered. Worse yet, the firm might continue to think the attributes that helped it attract the new customers also will help it retain them. In many instances, however, it would be a mistake to keep emphasizing the same attributes as customer needs evolve over time.

DAIM Many firms now offer consumption relationships—multiattribute offerings consumed in multiple episodes over time. Consider an automobile. At the broad levei, it consists of two attributes: the physical product (i.e., the car), and the associated dealership services consumed over time. Similarly, a mutual fund consists of such attributes as the fund's performance, the mutual fund adviser, and other interactions between the client and the firm. Moreover, these interactions and the fund's performance occur over time and are evaluated as such. The idea of a consumption relationship is inherently dynamic. As such, not only does performance on various attributes change over time, but also its impact on overall satisfaction also varies. As a result, the importance of a given attribute changes over time; as a consumer's duration of a consumption relationship changes, the performance on and importance of various attributes might change. When considering an automobile, for instance, ifs conceivable that during the first few months of consumption, attributes such as fit and finish, color, and styling are more important in determining overall satisfaction. Over time, however, attributes such as brakes, reliability, and engine performance might become more important in determining overall satisfaction. Similarly, the importance of dealership service might change. Such shifts in attribute importance have tactical and strategic implications for a firm, consisting of customer acquisition and retention, resource management, employee training, and relationship management.

With customer acquisition and retention, attributes that are important to newly acquired customers might differ from those that loyal customers consider important, in our analysis, a credit card company discovered that the format of the monthly billing statement was extremely important for newly acquired customers. But the format was not important to customers who had been with the firm for a long time (perhaps because they became used to it and took it for granted). With resource management, a firm can allocate differing levels of resources to customer acquisition or customer retention. If attributes have different levels of importance for newly acquired customers vs. loyal customers, firms can allocate their resources to various attributes accordingly. We found that a mutual fund firm was able to optimize its resources spent on employee training by emphasizing different attributes among newly acquired and loyal customers. In regard to employee training, employees can be trained to deal differently with customers based on the length of a customer's relationship with a firm. Such a strategy can be implemented by banks, mutual fund firms, insurance companies and the like for which such information is tracked in the internal database. As for relationship management, all of the above strategies can be used to design and manage customer relationships over a longtime horizon. Instead of market share emphasis, many firms have adopted a strategy of managing relationships with a limited customer base. By identifying how and understanding why different attributes contribute to overall satisfaction at different stages of the relationship, effective relationship management strategies can be devised. However, implementing these insights entails identifying changes in attribute importance over time, then systematically understanding the reason behind such changes. The practice followed in most satisfaction studies is to survey consumers at a given time, then to conduct a "key-driver analysis" to quantify attribute importance. Although some firms will segment based on demographic variables such as gender or age, very little attention is paid to the duration of a consumer's relationship with the firm. It's assumed that length of relationship does not moderate the importance of an attribute in determining overall satisfaction. Part of this may be a result of the lack of a systematic methodology for implementing these insights. We report a simple methodology to do this. The use of the methodology is illustrated with three cases. In each case, including the duration of a customer's relationship in understanding attribute importance, provided the client with valuable insights into satisfaction and retention-management programs.

Step 1: Determine and compare attribute importance for customers having relationships for different lengths of time. Data collected from a typical satisfaction survey can be used for this step. Attribute importance can be computed using a variety of methods, though we recommend the use of regression analysis. Of course, care must be taken to ensure that the attributes in question are distinct so that muiticollinearity is not an issue in the estimation. For comparison of attribute weights, two approaches are available; cross sectional, and longitudinal. With the cross-sectional approach, firms can segment the customer base into new and loyal customers based on data about the duration of their relationship with the firm. Note that, in this approach, a given customer can either be in the new or loyal group, but not both. It is important to use the right cutoff for classifying customers as "new" or "loyal." For instance, you might want to ensure that the cutoff you use Is acceptable to the marketing and sales department and can be implemented in the larger database. With the longitudinal approach, you would track the same customers over time. As the duration of a customer's relationship with the firm increases, the customer fills out a series of satisfaction surveys over time. For instance, a customer might fill out a satisfaction survey right after acquiring a car, three months into having the car, and after two years of ownership. Over time, the firm would have longitudinal evaluations of satisfaction. Attribute importance then can be statistically computed and compared for the three periods. Step 2: Create a graph for the attribute importance and initiate discussion. To ensure that the statistical information obtained from Step ! gets acted on, it's critical to plot the attribute importance over time. If there is one instance in which a picture is worth a thousand words, this is it. These charts should be shared among all the relevant managers and their input obtained regarding the differences in attribute importance. Step 3: Conduct qualitative research to discover reasons for changes in attribute importance. After managers have developed their theories about changes in attribute importance, it's also necessary to "consult" the customer. To do this, we recommend using an in-depth interview or focus groups. We've found eight to 10 in-depth interviews or two focus groups (one with new and one with loyal customers) to be sufficient. Naturally, each firm should adapt this guideline based on its needs.

Step 4: Initiate action. Finally, it's time to act on the insights obtained from the research. We emphasize that if people from different departments and functions are Involved in Step 2. the probability that they will act on the resuits increases astronomically. For instance, based on the length of a customer's relationship, a firm could segment its customer base and fine-tune its RESEARCH METHODOLOGY In our outline of a methodology for understanding the interaction with customers. In some cases, firms might train their dynamic nature of attribute importance, note that, after the sta- frontline employees to emphasize different aspects of the prodtistical computation (Steps 1 and 2), the qualitative follow-up uct or service depending on whether the customer is a newly research is critical to gain insights into why the attribute impor- acquired or loyal customer. tance changed. We also highlight the actionability of the research outcome. For the sake of readability, we omitted the CASE STUDY 1 : CREDIT CARD INDUSTRY details of the statistical analysis. Where appropriate, however, we Because of intense competition, managers in the credit card provided references for papers that used this methodology. industry need to continuously attract new customers while niarkeliiiii research

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retaining already acquired customers. But to what extent are the needs of new and loyal customers different? If they are different, what implications do such differences have for managing the customer base? To answer these questions, we analyzed data from an existing satisfaction study for a credit card company.

• The format of the statement and performance of the customer service representative are more important for new, rather than loyal customers, Conversely, the promotional benefits associated with the card and adequacy of credit limit were more important to loyal customers, than to new ones,

DATA & METHODOLOGY

• Interest rate is equally important to new and loyal customers and was considered a "core" attribute.

We analyzed data from 573 credit card holders. Among them, 31% had owned the credit card for less than a year (classified as new), and 69% had owned the card for more than one year (classified as loyai). Note that this study uses a cross-sectional approach and that the classification of customers as new or loyal based on a 1-year cutoff is highly subjective. We discussed this cutoff with the managers. They told us that in their experience, customers who have stayed with them for at least a year have a very low probability of switching; among new customers, the majority of defections occur within a year After that, the defection rate declines considerably. Ratings for attribute performance were obtained on a 5point scale (5=excellent, l=poor) for the following attributes: INT (interest rate charged), STM (format of the monthly statement), BEN (promotional benefits associated with the card), SRV (performance of the customer service representative), and CRE (adequacy of the credit limit). Attribute importance was computed using regression analysis. Statistical comparisons then were made to establish that the shift in importance occurring from chance alone was small (pice Research. 1 (February), 227-35. Hanson, Randy (1992), "Determining Attribute Importance," Quire's Marketing Research Review. 6 (October), 16-8

Mittal. Vikas, Pankaj Kumar and Michael T^iros (1999), " Attribute Performance, Satisfaction, and Behavioral Intentions Over Time: A Consumption System Approach," \ournal of Marketing, 63 (April), 88-101. •

•. lerome M. Katrichis, Frank E, Forkin, and Mark Konkel 11993), "Does Satisfaction with Multi-attribute Products Vary Over Time? A Performance Based Approach," Advances in Consumer Research, Chris T. Allen and Deborah Roedder lohn (eds.), vol. 21,412-17.

Rust, Roland T., Anthony |. Zahorik, and Timothy L Keiningham (1995), "Return on Quality (ROO): Making Service Quality Financially Accountable," \ournal of Marketing, 59 (April). 58-70ACKNOWLEDGMENTS

We thank Frank Forkin of I.D. Powers and Associates for his comments and for providing material for the third case study. We also thank Patrick M. Baldasare for providing materials for the first case study reported here.

customers: auto ownership experience Vikas Mittal is an assistant professor of marketing at the Katz Graduate School of Business, University of Pittsburgh. His research, which focuses on issues related to customer satisfaction, retention, and profitability, has appeared in such publica-

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tions as lournai of Marketing, ]oiirnal of Consumer Research, \ournalof Health Care Marketing, and Organization Studies. He also has cont r i b u t e d to CASRO journal. Financial Times, Marketing N w s . and Quirk's Marketing Research Review.

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lerome M. Katrichis is an assistant professor of marketing at the Barney School of Business, University of Hartford. His research focuses on issues related to business-to-business marketing, research methodology, and customer satisfaction. He has published in a variety of journals including Industrial Marketing Management, journal of Consumer Affairs, The journal of the Marketing Research Society, and Advances in Consumer Research.