Consumer Value-Maximizing Sweepstakes & Contests: A Theoretical and Experimental Investigation

Sweepstakes and contests are an extremely common promotional strategy used by firms. The sweepstakes and contests often differ significantly in the design of reward structure. For example, in 1999, Godiva Chocolates conducted a sweepstakes where one box of chocolates contained a diamond jewellery. The chance of winning was 1 in 320,000. In 2000, M&M conducted a contest where the Grand Prize of a 1,000,000 had winning odds of 1 in 380,000,000 and a million second prizes of a coupon redeemable for a M&M packet had the odds of 1 in 380. In a contest conducted by Planters in 2000, the first prize too was a 1 m (odds 1 in 5,000,000) but there were only 100 second prizes of a NFL football jacket with odds of 1 in 50,000. In 1999, Old Navy conducted a sweepstake where there were 4,552 first prize winners who got $100 gift cards with the odds of winning 1 in 1,000, the 9,105 second prize of$ 20 gift certificates had odds of 1 in 500 and the 13,660 third prizes of $10 certificates and 883,476 fourth prizes of$5 had winning odds of 1 in 333 and 1 in 50 respectively. These examples raise the issue of how reward structure would affect consumer valuation and participation. The objective of this paper is to obtain an understanding of how consumers' valuation of sweepstakes varies on the basis of differing consumer segments and the characteristics of the consumers. Our paper focuses on the decisions pertaining to the reward structure. We examine some commonly used sweepstakes and provide insights on how consumer valuations depend on the number of winners, the number of levels of prizes, and the difference in the awards between the levels (reward spread). We follow the Cumulative Prospect Theory to develop a model for consumer valuations of alternative formats of sweepstakes. The model applies a S-shaped probability weighting function and a loss-aversion framework for the consumers who switched to less preferred brands for sweepstakes but eventually did not win any prizes. We analytically derive our theoretical results and experimentally test some of the key implications. The results of the model show that the sweepstakes reward structure should be based on three factors: the objectives of the firm, the risk aversion of the customers, and the level of sub-additivity of probability weighting. The results of the model prescribes that the firm should begin by setting sweepstake objectives in terms of either attracting switchers or targeting current users. If the objective is to target current users, then the number of prizes awarded should be lower than in the case where the targets are switchers. If the current users are risk neutral, then the consumer value-maximizing award is a single grand prize. If the current users are risk averse, then the award should consist of multiple "large" prizes. When the firm's objective is to draw sales away from competitors, the value-maximizing strategy is to distribute the award money over more prizes. If the non-current user segment is risk neutral with respect to gains but sufficiently risk averse in the domain of losses, then the prescribed reward structure is to have a single grand prize but also include several small prizes which ideally should be close to the opportunity cost of the customers. If the non-loyal customers are risk averse in gain and loss averse, then the best prize allocation is to have both multiple large prizes as well as several small prizes.Another recommendation from the model analysis is that the firm should minimize the number of prizes at each level. In practice, the costs of implementing and communicating such a prize structure could be high. To trade-off between the logistical and communication costs and the theoretically value-maximizing approach, firms could increase the number of prizes at each level for easier implementation. A trade-off is involved between increasing the attractiveness of the sweepstake and the implementation costs of administering several levels of prizes. Often, when the prizes are products rather than cash, the firm may obtain quantity discounts for the products but the value of the products will be the same for the sweepstake participants.Sales promotion, prospect theory, customer loyalty ,

A Dyad Model of Calling Behaviour with Tie Strength Dynamics

This paper investigates the dynamic relation between callers' social ties and their wireless phone service consumption. We construct a large pair-level panel dataset with information on the number of each pair's common contacts, calling activities, prices, and each caller's characteristics over a one-year time period. We estimate a dynamic model that encapsulates the evolving relationship between each pair of consumers. We find the amount of communications between a pair of consumers increases with the strength of their tie, which is higher when these two consumers share more common contacts. Our results support the reciprocity rule in telephone calls, i.e. when individual A initiates more (less) phone calls to individual B in one month, their social tie will be strengthened (weakened) and individual B will make more (less) calls to individual A in the subsequent months. We demonstrate the implications of our results in evaluating the return of temporary price promotions and designing price plans. Our results underscore the importance of incorporating social network characteristics in the study of telecommunications markets

A Dyad Model of Calling Behaviour with Tie Strength Dynamics

This paper investigates the dynamic relation between callers' social ties and their wireless phone service consumption. We construct a large pair-level panel dataset with information on the number of each pair's common contacts, calling activities, prices, and each caller's characteristics over a one-year time period. We estimate a dynamic model that encapsulates the evolving relationship between each pair of consumers. We find the amount of communications between a pair of consumers increases with the strength of their tie, which is higher when these two consumers share more common contacts. Our results support the reciprocity rule in telephone calls, i.e. when individual A initiates more (less) phone calls to individual B in one month, their social tie will be strengthened (weakened) and individual B will make more (less) calls to individual A in the subsequent months. We demonstrate the implications of our results in evaluating the return of temporary price promotions and designing price plans. Our results underscore the importance of incorporating social network characteristics in the study of telecommunications markets

Choice Models and Customer Relationship Management

Customer relationship management (CRM) typically involves tracking individual customer behavior over time, and using this knowledge to configure solutions precisely tailored to the customers' and vendors' needs. In the context of choice, this implies designing longitudinal models of choice over the breadth of the firm's products and using them prescriptively to increase the revenues from customers over their lifecycle. Several factors have recently contributed to the rise in the use of CRM in the marketplacePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47023/1/11002_2005_Article_5892.pd

Designing Optimal Sales Contests: A Theoretical Perspective

Sales contests are commonly used by firms as a short-term motivational device to increase salespeople's efforts. Conceptually, sales contests and piece-rate schemes, such as salary, commission, or quotas, differ in that in sales contests payment to salespeople is based on relative rather than absolute sales levels. Using the agency theoretic framework where the firm is risk neutral and the salespeople are risk averse, we examine how a firm should design an optimal contest to maximize its profit through stimulating salespeople's efforts. Specifically, we investigate how many salespeople should be given awards and how the reward should be allocated between the winners. Three commonly used sales contest formats are studied. In the first format, termed as Rank-Order Tournament, there are many winners and the amount of reward is based on relative rank achieved, with larger amounts awarded to higher ranks. We also examine two special cases of Rank-Ordered Tournament: a Multiple-Winners format, where the reward is shared equally, and a Winner-Take-All format, where a single winner gets the entire reward. We model salespeople's behavior by considering utility of the reward from achieving one of the winning ranks in the contest and assessing incremental chances of winning by exerting more effort. The analysis was done for two situations based on whether the total reward is large enough for salespeople to participate in the effort-maximizing sales contest or not. The analysis shows that factors impacting contest design include the salespeople's degree of risk aversion, number of salespeople competing in the contest, and degree of sales uncertainty (which reflects strength of the sales-effort relationship). The results show that salespeople exert lower effort when there are larger numbers of participants or when sales uncertainty is high. We find that the Rank-Order Tournament is superior to the Multiple-Winners contest format. In a Multiple-Winners format, the salesperson whose performance is just sufficient to win is better off than any of the other winners as he exerts the least effort to win but obtains as high a reward as any other winners. Specific recommendations on contest designs are obtained assuming that sales follow either a logistic or uniform distribution. Assuming that sales outcome is logistically distributed and the contest budget is high enough to ensure participation, our analysis shows that the total number of winners in a sales contest should not exceed half the number of the contestants. This result is due to the symmetric nature of the logistic distribution. Our analysis also indicates that the total number of winners should be increased and the spread decreased when salespeople are more risk averse. When salespeople are more risk averse, their marginal values for higher rewards become smaller. The spread should increase with ranks when rate of risk tolerance is high and decrease with ranks when the rate of risk tolerance is lower. In the extreme case of risk-neutral salespeople, the optimal design is a Winner-Take-All format. We also conclude that since the probability of winning the contest decreases with number of contestants, the optimal number of winners should increase and interrank spread decrease when there are a larger number of participants. If the firm does not allocate a large enough budget for salespeople to participate in the effort-maximizing sales contest, then the firm may increase the number of winners to more than half the sales-force. Increasing the number of winners and decreasing the spread are required to encourage the salespeople to participate, particularly when there are many participants who are risk averse. A counterintuitive result is that the number of winners should be reduced and the spread increased when sales uncertainty is high. Increasing sales uncertainty leads to lower equilibrium effort levels while keeping the expected utility of the contest rewards the same. Therefore, increased uncertainty results in higher participation incentive. The firm should thus relatively reduce the number of winners in high-uncertainty situations. Under the assumption of uniformly distributed sales, the recommendation is that a Winner-Take-All contest induces maximum efforts regardless of the level of risk aversion, number of players, or the degree of uncertainty. When the Winner-Take-All format does not meet the participation constraint, our analysis recommends offering a big reward to the top salesperson and a small reward to many other sales-people. The small reward should be just sufficient to ensure that all salespeople participate. Consistent with logistic distribution, the spread should decrease when salespeople are more risk averse or there are more players but should increase when sales uncertainty is larger. These results highlight that some of the conclusions drawn may be sensitive to distributional assumptions.Agency Theory, Sales Contests, Salesforce Compensation