Raghuram Iyengar

A Model of Consumer Learning for Service Quality and Usage

In many services (e.g., the wireless service industry), consumers choose a service plan according to their expected consumption. In such situations, consumers experience two forms of uncertainty. First, they may be uncertain about the quality of their service provider and can learn about it after repeated use of the service. Second, they may be uncertain about their own usage of minutes and learn about it after observing their actual consumption. The authors propose a model to capture this dual learning process while accounting for the nonlinearity of the pricing scheme used in wireless services. The results show that both quality learning and quantity learning are important. The authors conduct several policy experiments to capture the effects of consumer learning, pricing, and service quality on customer lifetime value (CLV). They find that consumer learning can result in a win–win situation for both consumers and firm; consumers leave less minutes on the table, and the firm experiences an increase in overall CLV. For example, the authors find that there is a 35% increase (approximately

Do Friends Influence Purchases in a Social Network

75) in overall CLV with consumer learning than without. The key driver of this result is the change in the retention rate with and without learning.

Tricked by Truncation: Spurious Duration Dependence and Social Contagion in Hazard Models

Social networks, such as Facebook and Myspace have witnessed a rapid growth in their membership. Some of these businesses have tried an advertising-based model with very limited success. However, these businesses have not fully explored the power of their members to influence each other’s behavior. This potential viral or social effect can have significant impact on the success of these companies as well as provide a unique new marketing opportunity for traditional companies. However, this potential is predicated on the assumption that friends influence user’s behavior. In this study we empirically examine this issue. Specifically we address three questions - do friends influence purchases of users in an online social network; which users are more influenced by this social pressure; and can we quantify this social influence in terms of increase in sales and revenue. To address these questions we use data from Cyworld, an online social networking site in Korea. Cyworld users create mini-homepages to interact with their friends. These mini-homepages, which become a way of self-expression for members, are decorated with items (e.g., wallpaper, music), many of which are sold by Cyworld. Using 10 weeks of purchase and non-purchase data from 208 users, we build an individual level model of choice (buy - no-buy) and quantity (how much money to spend). We estimate this model using Bayesian approach and MCMC method. Our results show that there are three distinct groups of users with very different behavior. The low-status group (48% of users) are not well connected, show limited interaction with other members and are unaffected by social pressure. The middle-status group (40% users) is moderately connected, show reasonable non-purchase activity on the site and have a strong and positive effect due to friends’ purchases. In other words, this group exhibits “keeping up with the Joneses” behavior. On average, their revenue increases by 5% due to this social influence. The high-status group (12% users) is well connected and very active on the site, and shows a significant negative effect due to friends’ purchases. In other words, this group differentiates itself from others by lowering their purchase and strongly pursuing non-purchase related activities. This social influence leads to almost 14% drop in the revenue of this group. We discuss the theoretical and managerial implications of our results.

How Social Network and Opinion Leaders Affect the Adoption of New Products

We show both analytically and through Monte Carlo simulations that applying standard hazard models to right-truncated data, i.e., data from which all right-censored observations are omitted, induces spurious positive duration dependence and hence can trick researchers into believing to have found evidence of social contagion when there is none. Truncation also tends to deflate the effect of time-invariant covariates. These results imply that not accounting for right truncation can lead managers to rely too much on word of mouth in generating new product adoption and to poorly identify the customers most likely to adopt early. Not accounting for right truncation can also lead to suboptimal pricing decisions and to erroneous assessments of variations in customer lifetime value. We assess the effectiveness of four possible solutions to the problem and find that only using an analytically corrected likelihood function protects one against truncation artifacts inflating coefficients of contagion and attenuating coefficients of time-invariant covariates.

Rejoinder---Further Reflections on Studying Social Influence in New Product Diffusion

Abstract Do word-of-mouth and other peer influence processes really affect how quickly people adopt a new product? Can one identify the most influential customers and hence those who are good seeding points for a word-of-mouth marketing campaign? Can one also identify those customers most likely to be influenced by their peers? A pharmaceutical company seeking to improve its marketing effectiveness by leveraging social dynamics among physicians set out to answer these questions. There is indeed evidence of social influence, even after controlling for sales calls and individual characteristics. Also, people who are central in the network and those who use the product intensively are more influential. Finally, people who view themselves as opinion leaders are less affected by peer influence, whereas people who others really turn to for information or advice are not differentially affected. This last finding suggests that self-reported opinion leadership captures self-confidence, whereas a central position in the social network captures true leadership. Since sociometric techniques identify true opinion leaders more effectively than self-reports do, word-of-mouth programs targeting sociometric leaders are expected to be more effective than programs targeting self-reported leaders

A Conjoint Model of Quantity Discounts

Building on the commentaries on our work, we make additional suggestions for future research on social contagion and new product diffusion. In particular, we note that social contagion may occur for many reasons and that investigating how various personal or group characteristics moderate the amount of influence some customers exert or the extent to which others are sensitive to potential influence can provide insights into the social mechanism(s) at work.

Opinion Leadership and Social Contagion in New Product Diffusion

Quantity discount pricing is a common practice used by business-to-business and business-to-consumer companies. A key characteristic of quantity discount pricing is that the marginal price declines with higher purchase quantities. In this paper, we propose a choice-based conjoint model for estimating consumer-level willingness to pay (WTP) for varying quantities of a product and for designing optimal quantity discount pricing schemes. Our model can handle large quantity values and produces WTP estimates that are positive and increasing in quantity at a diminishing rate. In particular, we propose a tractable WTP function that depends on both product attributes and product quantity and that captures diminishing marginal WTP. We show how such a function embeds standard WTP functions in the quantity discount literature as special cases. We also demonstrate how to use the model to estimate the consumer value potential, which is the product of the premium a consumer is willing to pay and her volume potential. Finally, we propose a parsimonious experimental design approach for implementation. We illustrate the model using data from a conjoint study of online movie rental services. The empirical results show that the proposed model has good fit and predictive validity. In addition, we find that marginal WTP in this category decays rapidly with quantity. We also find that the standard choice-based conjoint model results in anomalous WTP distributions with negative WTP values and nondiminishing marginal willingness-to-pay curves. Finally, we identify four segments of consumers that differ in terms of magnitude of WTP and volume potential, and we derive optimal quantity discount schemes for a monopolist and a new entrant in a competitive market.