Abstract
Presented is an approach to classify a brand’s buyers into groups with varying degrees of loyalty along a continuum from “hard-core loyal” to “hard-core switcher.” A taxonomy is developed based on the joint use of stated consideration set and brand-switching data. In an empirical application to the automobile industry, classic stochastic models such as Grover-Srinivasan (J Mark Res 24:139–153, 1987) and Colombo-Morrison (Mark Sci 8(1):89–99, 1989), which attempt to recover the heterogeneity existing in the switching matrix overstate the number of hard-core loyals (buyers who repurchase with probability one) by 48% and 67%, respectively. The proposed taxonomy illuminates the sources of the overestimation and provides insights into the brand health of competing automotive makes.
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Notes
In their “Appendix,” GS discuss including heterogeneity within switching segments. Nevertheless, as the authors themselves state, the within-segment heterogeneity is not uniquely identified with switching data alone. The required long sequence of purchases per customer is not generally available for durable or infrequently purchased products.
We do not replicate switching-matrix-based models that do not specifically estimate a loyal segment for each brand (e.g., Jain et al. 1990).
The EBS 1997 clearly indicates that the survey is to be completed by “the principal purchaser” of the new vehicle. Fleet buyers are excluded as data comes from individuals sampled from car registration records.
The EBS 1997 survey truncates the revealed consideration set to a maximum of five self-reported vehicles. It might be argued that, for some switchers, the brand last purchased might have been the sixth or higher-order considered brand. If that were the case, the truncated consideration set will omit the last purchased brand. The truncation does not affect our conclusions for the HCL segment because the consideration set size criterion used to construct the taxonomy is a binary indicator corresponding to a set size of one or greater than one. Thus, the truncation could only result in an overestimation of the HS segment and an underestimation of the SS one. This will have no implications for the HCL, the SL, or the HCS segments. Moreover, in the EBS 1997 database, only 1.83% of the buyers reported considering five brands. Hence, the proportion of individuals who might have been forced to truncate their consideration set is very small.
The sizes of the n loyal segments in GS model are defined with respect to the total market sales and not conditional on the number of consumers trading in a particular car. Therefore, after estimating the GS model, we rescaled the sizes of these n loyal segments to make it comparable with the HCL segment sizes obtained with the CM model and the taxonomy framework. We used the following transformation rule:
\(\alpha _i = \frac{{V_i \, \times \,{\text{total}}\,{\text{sample}}\,{\text{size}}}}{{{\text{total}}\,{\text{trade}}\,{\text{in}}\,{\text{brand}}\,i}}\) where V i is the GS estimated proportion of buyers in the total market who are loyal to brand i.
Even though CM and GS differ in the number of switching segments, both models allow every switcher to consider all brands in the product class.
Suppose that a consumer is considering buying only brand A, CS = {A}. In this case, she will buy brand A with probability equal to 1, Pr(A) = 1. Suppose now that the same consumer is also considering brand B, CS = {A, B}. In this case, both brands have a positive probability of being chosen. For example, without loss of generality, we can assume that Pr(A) = 0.8 and Pr(B) = 0.2. Hence, Pr(A) < 1. We can safely say that her commitment to brand A decreases as we go from {A} to {A, B}. Now, suppose that in addition to brands A and B she also considers brand C, CS = {A, B, C}. In this case, we cannot say with certainty that the probability of buying brand A decreases with respect to that of {A, B}. It might well be the case that Pr(A) stays constant and that the positive probability of buying brand C is originated only at the expenses of a lower probability of buying brand B. Using the same example as above, Pr(A) = 0.8, Pr(B) = 0.1, and Pr(C) = 0.1. Therefore, we can only be certain of a decrease in the probability of buying brand A when we compare consideration sets of size one with sets of size two or more.
As some authors (e.g., Grover and Srinivasan 1987) have discussed in earlier research, the HCL segment could be further divided into n different segments, one for each of the n brands included in the analysis.
References
Aaker, D. A. (1996). Building strong brands. New York: Free Press.
Berry, S., Levinsohn, J., & Pakes, A. (2004). Differentiated products demand systems from a combination of micro and macro data: the new car market. Journal of Political Economy, 112(1), 68–105, part 1.
Blattberg, R. C., & Deighton, J. (1996). Manage marketing by the customer equity test. Harvard Business Review, 74(July/August), 136–144.
Blattberg, R. C., Getz, G., & Thomas, J. S. (2001). Customer equity: Building and managing relationships as valuable assets. Boston: Harvard Business School Press.
Colombo, R. A., & Morrison, D. G. (1989). A brand switching model with implications for marketing strategies. Marketing Science, 8(1), 89–99.
Colombo, R. A., Ehrenberg, A., & Sabavala, D. (2000). Diversity in analyzing brand-switching tables: The car challenge. Canadian Journal of Marketing Research, 19, 23–36.
Cooper, L. G., & Inoue, A. (1996). Building market structures from consumer preferences. Journal of Marketing Research, 33(3), 293–306. doi:10.2307/3152126.
Dall’Olmo Riley, F., Ehrenberg, A. S. C., Castleberry, S. B., Barwise, T. P., & Barnad, N. R. (1997). The variability of attitudinal repeat-rates. International Journal of Research in Marketing, 14, 437–450. doi:10.1016/S0167-8116(97)00023-2.
Dasgupta, S., Siddarth, S., & Silva-Risso, J. (2007). To lease or to buy? A structural model of consumer’s vehicle and contract choice decisions. Journal of Marketing Research, 44(August), 490–502. doi:10.1509/jmkr.44.3.490.
Ehrenberg, A. S. C., Goodhardt, G. J., & Barwise, T. P. (1990). Double jeopardy revisited. Journal of Marketing, 54(3), 82–91. doi:10.2307/1251818.
Fader, P. S., & Schmittlein, D. C. (1993). Excess behavioral loyalty for high-share brands: deviations from the Dirichlet model for repeat purchasing. Journal of Marketing Research, 30(November), 478–493. doi:10.2307/3172692.
Grover, R., & Srinivasan, V. (1987). A simultaneous approach to market segmentation and market structuring. Journal of Marketing Research, 24(May), 139–153. doi:10.2307/3151504.
Jacoby, J., & Chestnut, R. W. (1978). Brand loyalty measurement and management. New York: Wiley.
Jain, D., Bass, F. M., & Chen, Y. -M. (1990). Estimation of latent class models with heterogeneous choice probabilities: An application to market structuring. Journal of Marketing Research, 27(February), 94–101. doi:10.2307/3172555.
Keller, K. L. (1998). Strategic brand management: Building, measuring and managing brand equity. Upper Saddle River: Prentice Hall.
Lapersonne, E., Laurent, G., & Le Goff, J. -J. (1995). Consideration sets of size one: An empirical investigation of automobile purchases. International Journal of Research in Marketing, 12(1), 55–66. doi:10.1016/0167-8116(95)00005-M.
McPhee, W. N. (1963). Formal theories of mass behavior. New York: Free Press.
Reichheld, F., & Teal, T. (1996). The loyalty effect: The hidden force behind growth, profits, and lasting value. Boston: HBS.
Roberts, J. H., & Lattin, J. M. (1997). Consideration: Review of research and prospects for future insights. Journal of Marketing Research, 34(August), 406–410. doi:10.2307/3151902.
Rust, R. T., Zeithaml, V. A., & Lemon, K. N. (2000). Driving customer equity how customer lifetime value is reshaping corporate strategy. New York: Free Press.
Shocker, A. D., Ben-Akiva, M., Boccara, B., & Nedungadi, P. (1991). Consideration set influences on consumer decision-making and choice: Issues, models and suggestions. Marketing Letters, 2(3), 181–197.
Siddarth, S., Bucklin, R. E., & Morrison, D. G. (1995). Making the cut: Modeling and analyzing choice set restriction in scanner panel data. Journal of Marketing Research, 32(3), 255–266. doi:10.2307/3151979.
Silva-Risso, J., & Ionova, I. (2008). A nested logit model of product and transaction-type choice for planning automakers’ pricing and promotions. Marketing Science, 27(4), 545–566. doi:10.1287/mksc.1080.0374.
Train, K. E., & Winston, C. (2007). Vehicle choice behavior and the declining market share of U.S. automakers. International Economic Review, 48(4), 1469–1496.
Acknowledgments
The authors thank Marge Samuelson from JD Power and Associates for providing the data used in this study. The authors also thank the coeditor, Joe Urbany, and two anonymous reviewers for helpful comments.
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Appendix
Appendix
1.1 Detailed description of the steps to construct the taxonomy given in Fig. 1
Step 1: This step examines whether consumers reconsider the brand previously purchased and classifies them into one of two groups: loyal customers (brand previously purchased is in the consideration set) and disloyal customers (brand previously purchased is not reconsidered).
Step 2: In our second step, we distinguish consumers with the highest level of commitment (i.e., consideration set of size one, which implies a probability of purchasing the considered brand equal to one) from those who show lower levels of commitment (i.e., consideration set of size greater than one, which implies a probability of purchase for any considered brand less than one). We propose this binary classification because we can be certain only of a decrease in the purchase probability for a considered brand when we compare consideration sets of size one with sets greater than one.Footnote 7
Combining the information about consideration set size with the information about consideration set content, we further divide the two step 1 segments into four segments. Consumers who reconsider the previous brand purchased (i.e., loyal consumers) are further divided into HCL and Potential Switchers (PS). The first group consists of those individuals who only consider and therefore buy the brand previously purchased.Footnote 8 These HCL consumers present the highest level of commitment and loyalty possible. Potential Switchers are those who consider not only the previous brand purchased but also others. Therefore, a PS can either repeat the brand previously purchased or switch to one of the other considered brands. It is important to distinguish between this definition of PS and the one used by previous loyalty models (e.g., Colombo and Morrison 1989). In our taxonomy, if a consumer shops around for different brands (i.e., consideration size greater than one) that is a necessary but not sufficient condition to become a PS. To be a PS, a consumer needs to reconsider her previous choice. When she does not reconsider that choice (i.e. disloyal), she switches with probability equal to one. Hence, she is a sure switcher as opposed to a potential one.
We also apply the same consideration set size and content criterion to those customers who do not reconsider the previous brand purchased (i.e., disloyal customers in our first step). By doing so, disloyals are divided into two segments: HCS and Hard Switchers (HS). Individuals who only consider one brand—different from the previous brand purchased—are called HCS. Those who consider more than one brand but who do not reconsider the brand previously purchased are labeled HS.
From a behavioral loyalty perspective, the separation of the disloyal customers into HS and HCS might seem unnecessary because both types are sure switchers. On the other hand, HS and HCS consumers have different types of switching behaviors that could yield different implications for strategy. For example, while it might be worthwhile to try to retain an HS because they at least show a willingness to consider multiple brands, it might be too expensive to try to retain an HCS. Moreover, as we discuss, ignoring that these two segments differ in the probability of buying a new brand is one source of possible misspecification of the CM and GS brand-switching models.
The four resulting, mutually exclusive, segments from step 2 are: hard-core loyal, potential switchers, hard switchers, and hard-core switchers. They differ on repeat-consideration behavior and on the size of their consideration set.
Step 3: The final step incorporates information about the choice outcome. Using choice, the PS segment is divided into SL and SS. After evaluating all considered brands, soft loyals end up repurchasing the previous brand. Soft switchers are those consumers who reconsider the previous brand but end up switching. Note that for the HCL and HCS segments there is only one brand considered. Thus, there is no uncertainty regarding the choice outcome (conditional on a purchase having been made). Consumers in the HS segment consider multiple brands but do not reconsider the brand previously purchased. Consequently, knowing which brand they ultimately select does not alter the loyalty implications for the focal brand.
To summarize, in the loyalty taxonomy for a given brand, every previous buyer of that brand is assigned to one and only one of five mutually exclusive segments: (1) hard-core loyal, (2) soft loyal, (3) soft switcher, (4) hard switcher, and (5) hard-core switcher.
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Terech, A., Bucklin, R.E. & Morrison, D.G. Consideration, choice, and classifying loyalty. Mark Lett 20, 209–225 (2009). https://doi.org/10.1007/s11002-008-9065-y
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DOI: https://doi.org/10.1007/s11002-008-9065-y