Accounting for heterogeneity and dynamics in the loyalty-price sensitivity relationship

Abstract Marketers have been interested in the relationship between brand loyalty and price sensitivity for many years and have examined whether loyalty reduces consumer price sensitivity. The results, to date, indicate that loyalty does indeed raise the price that consumers are willing to pay for a brand. Other than this broad finding, however, there has been little research in the literature regarding whether and how this relationship varies across consumers and product categories and, within consumers, over time. This is the issue that we investigate in this paper. Specifically, we examine whether the price sensitivity–loyalty relationship is heterogeneous and dynamic. We propose an approach wherein the price sensitivity parameter of a brand choice model is specified as a function of loyalty with three parameters. The first parameter of this function represents the maximum possible reduction in price sensitivity due to loyalty. The second parameter affects the type and shape of the relationship between price sensitivity and loyalty. In particular, depending on the value of this parameter, the relationship could be non-existent, follow a concave shape, indicating decreasing response to increases in loyalty, or be S-shaped to capture the case of increasing response initially followed by decreasing response subsequently. Finally, the third parameter captures the rate at which price sensitivity falls as loyalty increases. We use the proposed approach to investigate the relationship in four frequently purchased categories. In each category, we select a sample of households and calibrate the model on the choices of all the households in the sample. We next employ an Empirical Bayes approach to obtain household-level estimates of all the parameters. These parameters are then used to assign each household in each category to a no response or concave or S-shaped response groups. Within each of these three groups, we assign each household to one of four different response level and rate segments, that is, high response–high rate, high response–low rate, low response–high rate, and low response–low rate. Each of these segments differs in the response level, that is, the maximum reduction in price sensitivity as loyalty reaches a maximum—and the response rate, that is, how quickly price sensitivity falls with increases in loyalty. Following the assignment of each household to a segment in each category, we pool the households across all four categories and calibrate a membership function. This function explains households’ membership in different segments in terms of product category characteristics, household demographics, the household’s responses to price, display, and feature promotions and the evolution of loyalty of the household. Our findings suggest that the nature of the loyalty–price sensitivity relationship does vary across consumers as well as over time. Specifically, the concave response is more likely than the S-shaped response or the absence of a response. We find that the S-shaped response is not related to responsiveness to in-store promotions. It is, however, associated with a slower growth in loyalty to a brand as it is purchased. The concave response, on the other hand, is associated with responsiveness to feature promotions but is unrelated to how loyalty to brands evolves with their purchases. We also find that demographic characteristics are related to the behavior of the concave and S-shaped responses. Specifically, for the S-shaped response, household demographics are related to both the maximum level of the curve as well as its rate of growth. In particular, the curve grows faster with age and its maximum increases with the weekly working hours of the household. In the case of the concave response, high income and more working hours raise the maximum level that the curve achieves. Its rate of growth, however, is unaffected by demographics. We also provide several managerial implications for loyalty and promotional programs based on our findings. Specifically, our first finding—that the loyalty–price sensitivity relationship is dynamic—suggests that, rather than having promotional programs, where the value of the price promotion is fixed and some consumers are targeted with the promotion while others are not, managers should have an entire schedule of price promotions with each level of promotions targeting consumers at a different loyalty level. Our second finding that the nature of the loyalty–price sensitivity relationship is heterogeneous across consumers suggests that designing loyalty programs on the basis of crude classifications such as loyals and non-loyals is not appropriate. Instead, households that are identified as loyal, need to be further divided based on how the loyalty affects their price sensitivity. Promotional programs should then be based on the specific type of relationship that a household exhibits. The third finding that the reductions in price sensitivity to loyalty can exhibit an S-shaped or a concave pattern also has an interesting managerial implication. Specifically, given the differences between the two patterns in how long it might take a consumer to reach a point where s(he) is willing to purchase a brand due to loyalty rather than due to a price promotion, and hence be a profitable customer, it may be preferable for managers to invest more in consumers who exhibit a concave rather than an S-shaped response. Finally, our result that different categories may exhibit different patterns of the relationship between price sensitivity and loyalty implies that each category needs to be analyzed by itself for what the nature of the loyalty–price sensitivity relationship is likely to be so that the most appropriate program for that category can be developed.