Baohong Sun

Cross-selling sequentially ordered products : An application to consumer banking services

Customers have predictable life cycles. As a result of these life cycles, firms that sell multiple products or services frequently observe that, in general, certain items are purchased before others. This predictable phenomenon provides opportunities for firms to cross-sell additional products and services to existing customers. This article presents a structural multivariate probit model to investigate how customer demand for multiple products evolves over time and its implications for the sequential acquisition patterns of naturally ordered products. The authors investigate customer purchase patterns for products that are marketed by a large midwestern bank. Among the substantive findings are that women and older customers are more sensitive to their overall satisfaction with the bank than are men and younger customers when determining whether to purchase additional financial services, and households whose head has a greater level of education or is male move more quickly along the financial maturity continuum than do households whose head has less education or is female.

A Dynamic Model of Brand Choice When Price and Advertising Signal Product Quality

In this paper, we develop a structural model of household behavior in an environment where there is uncertainty about brand attributes and both prices and advertising signal brand quality. Four quality signaling mechanisms are at work: 1 price signals quality, 2 advertising frequency signals quality, 3 advertising content provides direct but noisy information about quality, and 4 use experience provides direct but noisy information about quality. We estimate our proposed model using scanner panel data on ketchup. If price is important as a signal of brand quality, then frequent price promotion may have the unintended consequence of reducing brand equity. We use our estimated model to measure the importance of such effects. Our results imply that price is an important quality-signaling mechanism and that frequent price cuts can have significant adverse effects on brand equity. The role of advertising frequency in signaling quality is also significant, but it is less quantitatively important than price. In the printed version of Marketing Science, Vol. 27, No. 6, Erdem et al. 2008 was mistakenly identified as a Research Note. It is a regular article and has been corrected here and in the online table of contents.

An Empirical Investigation of the Spillover Effects of Advertising and Sales Promotions in Umbrella Branding

The authors investigate and find evidence for advertising and sales promotion spillover effects for umbrella brands in frequently purchased packaged product categories. The authors also capture the impact of advertising (as well as use experience) on both utility mean and variance across two categories. They show that variance of the random component of utility declines over time on the basis of advertising (and use experience) in either category. This constitutes the first empirical evidence for the uncertainty-reducing role of advertising across categories for umbrella brands.

Measuring the Impact of Promotions on Brand Switching When Consumers Are Forward- Looking

Logit choice models have been used extensively to study promotion response. This article examines whether brand-switching elasticities derived from these models are overestimated as a result of rational consumer adjustment of purchase timing to coincide with promotion schedules and whether a dynamic structural model can address this bias. Using simulated data, the authors first show that if the structural model is correct, brand-switching elasticities are overestimated by stand-alone logit models. A nested logit model improves the estimates, but not completely. Second, the authors estimate the models on real data. The results indicate that the structural model fits better and produces sensible coefficient estimates. The authors then observe the same pattern in switching elasticities as they do in the simulation. Third, the authors predict sales assuming a 50% increase in promotion frequency. The reduced-form models predict much higher sales levels than does the dynamic structural model. The authors conclude that reduced-form model estimates of brand-switching elasticities can be overstated and that a dynamic structural model is best for addressing the problem. Reduced-form models that include incidence can partially, though not completely, address the issue. The authors discuss the implications for researchers and managers.

Understanding Reference-Price Shoppers: A Within- and Cross-Category Analysis

The authors attempt to draw profiles of reference-price shoppers. Specifically, the authors study how selected factors that affect brand choice are correlated with consumer sensitivity to gains and losses with respect to internal reference prices. They also study the interaction between sociodemographics and gain and loss sensitivity. Furthermore, the authors analyze cross-category correlations in gain and loss sensitivity to shed light on their individual- and category-specific characters. In three categories, the results show significant heterogeneity in loss sensitivity among consumers and indicate that loss sensitivity is greater and more heterogeneous than gain sensitivity. Across categories, the results show that loss-sensitive shoppers are less influenced by past brand use and that both loss- and gain-sensitive shoppers more sensitive to price, display, and feature than the average consumer. Loss-sensitive households tend to be larger, and their heads are less likely to be fully employed, whereas gain-sensitive households have no clear demographic profile. The authors also discuss the limitations of latent-class models in profiling consumer segments and show how these problems are overcome using models with continuous, correlated multivariate distributions.

Cross-Selling the Right Product to the Right Customer at the Right Time

Firms are challenged to improve the effectiveness of cross-selling campaigns. The authors propose a customer-response model that recognizes the evolvement of customer demand for various products; the possible multifaceted roles of cross-selling solicitations for promotion, advertising, and education; and customer heterogeneous preference for communication channels. They formulate cross-selling campaigns as solutions to a stochastic dynamic programming problem in which the firms goal is to maximize the long-term profit of its existing customers while taking into account the development of customer demand over time and the multistage role of cross-selling promotion. The model yields optimal cross-selling strategies for how to introduce the right product to the right customer at the right time using the right communication channel. Applying the model to panel data with cross-selling solicitations provided by a national bank, the authors demonstrate that households have different preferences and responsiveness to cross-selling solicitations. In addition to generating immediate sales, cross-selling solicitations also help households move faster along the financial continuum (educational role) and build up goodwill (advertising role). A decomposition analysis shows that the educational effect (83%) largely dominates the advertising effect (15%) and instantaneous promotional effect (2%). The cross-selling solicitations resulting from the proposed framework are more customized and dynamic and improve immediate response rate by 56%, long-term response rate by 149%, and long-term profit by 177%.

Missing price and coupon availability data in scanner panels: Correcting for the self-selection bias in choice model parameters

Discrete choice models have been widely estimated on scanner panel data to study consumer choice. One challenge in scanner panel research is that only the prices of the items bought are recorded. The ad hoc models used to fill in the missing prices of non-purchased brands may create a self-selection bias in estimating consumer price sensitivities. This type of bias is also present in existing studies of coupon effects. To obtain consistent estimates of price elasticities in the presence of missing price and coupon values, we estimate a brand choice model jointly with models for the price and coupon processes.

The Impact of Advertising on Consumer Price Sensitivity in Experience Goods Markets

In this paper we use Nielsen scanner panel data on four categories of consumer goods to examine how TV advertising and other marketing activities affect the demand curve facing a brand. Advertising can affect consumer demand in many different ways. Becker and Murphy (Quarterly Journal of Economics 108:941–964, 1993) have argued that the “presumptive case” should be that advertising works by raising marginal consumers’ willingness to pay for a brand. This has the effect of flattening the demand curve, thus increasing the equilibrium price elasticity of demand and the lowering the equilibrium price. Thus, “advertising is profitable not because it lowers the elasticity of demand for the advertised good, but because it raises the level of demand.” Our empirical results support this conjecture on how advertising shifts the demand curve for 17 of the 18 brands we examine. There have been many prior studies of how advertising affects two equilibrium quantities: the price elasticity of demand and/or the price level. Our work is differentiated from previous work primarily by our focus on how advertising shifts demand curves as a whole. As Becker and Murphy pointed out, a focus on equilibrium prices or elasticities alone can be quite misleading. Indeed, in many instances, the observation that advertising causes prices to fall and/or demand elasticities to increase, has misled authors into concluding that consumer “price sensitivity” must have increased, meaning the number of consumers’ willing to pay any particular price for a brand was reduced—perhaps because advertising makes consumers more aware of substitutes. But, in fact, a decrease in the equilibrium price is perfectly consistent with a scenario where advertising actually raises each individual consumer’s willingness to pay for a brand. Thus, we argue that to understand how advertising affects consumer price sensitivity one needs to estimate how it shifts the whole distribution of willingness to pay in the population. This means estimating how it shifts the shape of the demand curve as a whole, which in turn means estimating a complete demand system for all brands in a category—as we do here. We estimate demand systems for toothpaste, toothbrushes, detergent and ketchup. Across these categories, we find one important exception to conjecture that advertising should primarily increase the willingness to pay of marginal consumers. The exception is the case of Heinz ketchup. Heinz advertising has a greater positive effect on the WTP of infra-marginal consumers. This is not surprising, because Heinz advertising focuses on differentiating the brand on the “thickness” dimension. This is a horizontal dimension that may be highly valued by some consumers and not others. The consumers who most value this dimension have the highest WTP for Heinz, and, by focusing on this dimension; Heinz advertising raises the WTP of these infra-marginal consumers further. In such a case, advertising is profitable because it reduces the market share loss that the brand would suffer from any given price increase. In contrast, in the other categories we examine, advertising tends to focus more on vertical attributes.

Why Do Consumers Buy Extended Service Contracts

We examine purchases of extended service contracts, which are essentially insurance products, for electronic products in a retail setting. The primary insurance purchase determinants are perceived probability of loss, extent of loss, risk aversion, and amount of insurance premium. We examine how product characteristics (hedonic/utilitarian, manufacturers warranty) and retailer actions (promotions, feature advertising) influence the purchase of extended service contracts. We also investigate the impact of consumer characteristics (income, gender, and prior usage) on these insurance purchase determinants. To test the predictions, we use revealed preferences from panel data of electronic purchases across several product categories. (c) 2009 by JOURNAL OF CONSUMER RESEARCH, Inc..

Testing for Choice Dynamics in Panel Data

This article applies different approaches to distinguish state dependence from unobserved heterogeneity and serial correlation and, hence, test for state dependence in consumer brand choices. First, we apply a simple method proposed by Chamberlain, which involves lagged exogenous variables only. Second, we also estimate a lagged-dependent-variable specification proposed by Wooldridge. Third, we use the estimation approach suggested by Wooldridge to estimate a model with both lagged dependent and exogenous variables to distinguish between the two different sources of choice dynamics, state dependence and lagged effects of the exogenous variables. Our analysis reveals that the best approach is to use models with both lagged dependent and exogenous variables. Our findings include strong evidence for state dependence in five out of the six product categories studied in this article.