Our objective in this paper is to measure the impact valence, volume, and variance of national online user reviews on designated market area DMA-level local geographic box office performance of mov...
Customer retention and customer churn are key metrics of interest to marketers, but little attention has been placed on linking the different reasons for which customers churn to their value to a contractual service provider. In this paper, we put forth a hierarchical competing-risk model to jointly model when customers choose to terminate their service and why. Some of these reasons for churn can be influenced by the firm e.g., service problems or price--value trade-offs, but others are uncontrollable e.g., customer relocation and death. Using this framework, we demonstrate that the impact of a firm's efforts to reduce customer churn for controllable reasons is mitigated by the prevalence of uncontrollable ones, resulting in a “damper effect” on the return from a firm's retention marketing efforts. We use data from a provider of land-based telecommunication services to demonstrate how the competing-risk model can be used to derive a measure of the incremental customer value that a firm can expect to accrue through its efforts to delay churn, taking this damper effect into account. In addition to varying across customers based on geodemographic information, the magnitude of the damper effect depends on a customer's tenure to date. We discuss how our framework can be used to tailor the firm's retention strategy to individual customers, both in terms of which customers to target and when retention efforts should be deployed.
A variable annuity is a popular product for investing retirement income. However, thousands of similar-looking variable annuity products are being offered by hundreds of financial service companies. In such a scenario, how can Prudential achieve meaningful product differentiation to increase the sales of its variable annuities? The solution led to the development and implementation of the “Emotion Quotient” (EQ) Tool. The EQ Tool enabled Prudential to redefine its marketing and sales approach along a proactive (as opposed to responsive) market orientation paradigm. This was accomplished by first using the EQ Tool to uncover and quantify the prevalence of certain emotions (such as fear and regret) in the prospective consumer and then pitching relevant variable annuity product(s) that could mitigate the specific behavioral risk corresponding to the prevalent emotion(s). This approach, which was backed by extensive research (as described in this study), enabled Prudential to gain over $450 million lift in variable annuity sales and contributed to consumer welfare by promoting awareness of behavioral risk to investors who are within five years of their retirement. This research study illustrates how industry can collaborate with academia to successfully apply marketing science to solve real-world business problems.
We argue that the Zeithammer and Adams paper [Zeithammer, R., C. Adams. 2010. The sealed-bid abstraction in online auctions. Marketing Sci. 29(6) 964–987] successfully documents consistent patterns in eBay bidding data that cast doubt on the common assumption that bidders in such auctions follow a “bid = value” strategy. These anomalies lend support to the authors' alternative model in which some bidders bid reactively and consequently bid below their valuation most of the time. The consistency of the authors' findings as well as the ability of their alternative explanation to account for all of their test results lends great support to their thesis. However, we think that several of their empirical tests examine ancillary assumptions about bidder behavior and do not test the bid = value assumption directly. Furthermore, although their reduced-form model incorporating “reactive” bidders is a good first attempt at expanding the canonical framework, we worry that their counterfactual pricing analysis using the reactive model is suspect because the parameters they estimate are not structural. Overall, the Zeithammer and Adams paper is a carefully argued critique of empirical methods used to study online auctions and provides valuable ideas to improve on these methods.
Despite the economic significance of the theme park industry and the huge investments needed to set up new attractions, no marketing models exist to guide these investment decisions. This study addresses this gap in the literature by estimating a response model for theme park attendance. The model not only determines the contribution of each attraction to attendance, but also how this contribution is distributed within and across years. The model accommodates saturation effects, which imply that the impact of a new attraction is smaller if similar attractions are already present. It also captures reinforcement effects, meaning that a new attraction may reinforce the drawing power of similar extant attractions, especially when these were introduced recently. The model is calibrated on 25 years of weekly attendance data from the Efteling, a leading European theme park. Our return on investment calculations show that it is more profitable to invest in multiple smaller attractions than in one big one. This finding is in remarkable contrast with the current “arms race” in the industry. Furthermore, even though thrill rides tend to be more effective than theme rides, there are conditions under which one should consider to switch to the latter.
Brand preferences and marketplace demand are a reflection of the importance of underlying needs of consumers and the efficacy of product attributes for delivering value. Dog owners, for example, may look to dog foods to provide specific benefits for their pets (e.g., shiny coats) that may not be available from current offerings. An analysis of consumer wants for these consumers would reveal weak demand for product attributes resulting from low efficacy, despite the presence of strong latent interest. The challenge in identifying such unmet demand is in distinguishing it from other reasons for weak preference, such as general noninterest in the category and heterogeneous tastes. We propose a model for separating out these effects within the context of conjoint analysis, and we demonstrate its value with data from a national survey of toothpaste preferences. Implications for product development and reformulation are explored.
In certain categories, an important element of competition is the use of previews to signal information to potential consumers about product attributes. For example, the front page of a newspaper provides a preview to potential newspaper buyers before they purchase the product. In this context, a news provider can provide previews that are highly informative about the content of the news product. Conversely, a news provider can utilize a preview that is relatively uninformative. We examine the incentives that firms have to adopt different preview strategies in a context where they do not have complete control of product positioning. Our analysis shows that preview strategy can be a useful source of differentiation. However, when a firm adopts a strategy of providing informative previews, it confers a positive externality on a competitor that utilizes uninformative previews. This reinforces the incentive of the competitor to use uninformative previews and explains why the market landscape in news provision is often characterized by asymmetric competition.
The idea of hierarchical, sequential, or intermediate effects has long been posited in textbooks and academic literature. Hierarchical effects occur when relationships among variables are mediated through other variables. Challenges in studying hierarchical effects in marketing include the large number of items present in most commercial studies and the presence of heterogeneous relationships among the variables. Existing approaches have dealt with the large number of variables by employing a factor structure representation of the data and have used standard mixture distributions for representing different response segments. In this paper, we propose a Bayesian model for the analysis of hierarchical data using the actual response items and incorporating heterogeneity that better reflects consumer stages in a decision process. Cross-sectional data from a national brand-tracking study are used to illustrate our model, where we find empirical support for a hierarchical relationship among media recall, brand beliefs, and intended actions. We find these effects to be insignificant when measured with standard models and aggregate analyses. The proposed model is useful for understanding the influence of variables that lead to intermediate as opposed to direct effects on brand choice.
The use of a durable good is limited by both its physical life and usable life. For example, an electric-car battery can last for five years (physical life) or 100,000 miles (usable life), whichever comes first. We propose a framework for examining how a profit-maximizing firm might choose the usable life, physical life, and selling price of a durable good. The proposed framework considers differences in usage rates and product valuations by consumers and allows for the effects of technological constraints and product obsolescence on a product's usable and physical lives. Our main result characterizes a relationship between optimal price, cost elasticities, and opportunity costs associated with relaxing upper bounds on usable and physical lives. We describe conditions under which either usable life or physical life, or both, obtains its maximum possible values; examine why a firm might devote effort to relaxing nonbinding constraints on usable life or physical life; consider when price cuts might be accompanied with product improvements; and examine how a firm might be able to cross-subsidize product improvements.
Reverse pricing is a market mechanism under which a consumer's bid for a product leads to a sale if the bid exceeds a hidden acceptance threshold the seller has set in advance. The seller faces two key decisions in designing such a mechanism. First, he must decide where in the process to collect the revenue—that is, whether to commit to a minimum markup above cost (and thus define the bid-acceptance threshold given cost) and whether to set a fee for the consumer's right to bid. Second, the seller must decide whether to facilitate or hinder consumer learning about the current bid-acceptance threshold. We analyze these decisions for a profit-maximizing small intermediary retailer selling to consumers who can also purchase the product in an outside posted-price market. The optimal revenue model is to charge a fee for the right to bid and then accept all bids above cost, rather than to set a positive minimum markup above cost. Avoiding minimum markups in favor of a bidding fee is more profitable because of increased efficiency arising from more entry by consumers and higher bids by the entrants. When consumers learn about the bid-acceptance threshold before they enter the market, efficiency increases further, and generating revenue through a bidding fee can compensate the seller for his loss of information rent when the competition from the outside posted-price firm is relatively weak.