Eva Ascarza

When Talk is 'Free': The Effect of Tariff Structure on Usage under Two- and Three-Part Tariffs

In many service industries, firms introduce three-part tariffs to replace or complement existing two-part tariffs. In contrast with two-part tariffs, three-part tariffs offer allowances, or “free” units of the service. Behavioral research suggests that the attributes of a pricing plan may affect behavior beyond their direct cost implications. Evidence suggests that customers value free units above and beyond what might be expected from the change in their budget constraint. Nonlinear pricing research, however, has not considered such an effect. The authors examine a market in which three-part tariffs were introduced for the first time. They analyze tariff choice and usage behavior for customers who switch from two-part to three-part tariffs. The findings show that switchers significantly “overuse” in comparison with their prior two-part tariff usage. That is, they attain a level of consumption that cannot be explained by a shift in the budget constraint. The authors estimate a discrete/continuous model of tariff choice and usage that accounts for the valuation of free units. The results show that the majority of three-part-tariff users value minutes under a three-part tariff more than they do under a two-part tariff. The authors derive recommendations for how the provider can exploit these insights to further increase revenues.

A Joint Model of Usage and Churn in Contractual Settings

As firms become more customer-centric, concepts such as customer equity come to the fore. Any serious attempt to quantify customer equity requires modeling techniques that can provide accurate multiperiod forecasts of customer behavior. Although a number of researchers have explored the problem of modeling customer churn in contractual settings, there is surprisingly limited research on the modeling of usage while under contract. The present work contributes to the existing literature by developing an integrated model of usage and retention in contractual settings. The proposed method fully leverages the interdependencies between these two behaviors even when they occur on different time scales or “clocks”, as is typically the case in most contractual/subscription-based business settings. We propose a model in which usage and renewal are modeled simultaneously by assuming that both behaviors reflect a common latent variable that evolves over time. We capture the dynamics in the latent variable using a hidden Markov model with a heterogeneous transition matrix and allow for unobserved heterogeneity in the associated usage process to capture time-invariant differences across customers. The model is validated using data from an organization in which an annual membership is required to gain the right to buy its products and services. We show that the proposed model outperforms a set of benchmark models on several important dimensions. Furthermore, the model provides several insights that can be useful for managers. For example, we show how our model can be used to dynamically segment the customer base and identify the most common “paths to death” i.e., stages that customers go through before churn.

The Perils of Proactive Churn Prevention Using Plan Recommendations: Evidence from a Field Experiment

Facing the issue of increasing customer churn, many service firms have begun recommending pricing plans to their customers. One reason behind this type of retention campaign is that customers who subscribe to a plan suitable for them should be less likely to churn because they derive greater benefits from the service. In this article, the authors examine the effectiveness of such retention campaigns using a large-scale field experiment in which some customers are offered plan recommendations and some are not. They find that being proactive and encouraging customers to switch to cost-minimizing plans can, surprisingly, increase rather than decrease customer churn: whereas only 6% of customers in the control condition churned during the three months following the intervention, 10% did so in the treatment group. The authors propose two explanations for how the campaign increased churn, namely, (1) by lowering customers’ inertia to switch plans and (2) by increasing the salience of past-usage patterns among potential churners. The data provide support for both explanations. By leveraging the richness of their field experiment, the authors assess the impact of targeted encouragement campaigns on customer behavior and firm revenues and derive recommendations for service firms.

Beyond the Target Customer: Social Effects of Customer Relationship Management Campaigns

Customer relationship management (CRM) campaigns have traditionally focused on maximizing the profitability of the targeted customers. The authors demonstrate that in business settings characterized by network externalities, a CRM campaign that is aimed at changing the behavior of specific customers propagates through the social network, thereby also affecting the behavior of nontargeted customers. Using a randomized field experiment involving nearly 6,000 customers of a mobile telecommunication provider, they find that the social connections of targeted customers increase their consumption and become less likely to churn, due to a campaign that was neither targeted at them nor offered them any direct incentives. The authors estimate a social multiplier of 1.28. That is, the effect of the campaign on first-degree connections of targeted customers is 28% of the effect of the campaign on the targeted customers. By further leveraging the randomized experimental design, the authors show that, consistent with a network externality account, the increase in activity among the nontargeted but connected customers is driven by the increase in communication between the targeted customers and their connections, making the local network of the nontargeted customers more valuable. These findings suggest that in targeting CRM marketing campaigns, firms should consider not only the profitability of the targeted customer but also the potential spillover of the campaign to nontargeted but connected customers.

Beyond the Target Customer: Social Effects of CRM Campaigns

Customer Relationship Management (CRM) campaigns have traditionally focused on maximizing the profitability of the targeted customers. In this paper we investigate the social effects of CRM campaigns. We demonstrate that, in business settings that are characterized by network externalities, a CRM campaign that is aimed at changing the behavior of specific customers propagates through the social network, thereby also affecting the behavior of non-targeted customers. Using a randomized field experiment involving nearly 6,000 customers of a mobile telecommunications provider, we find that the social connections of targeted customers increase their consumption and are less likely to churn due to a campaign that was neither targeted at them nor offered them any direct incentives. We estimate a social multiplier of 1.28. That is, the effect of the campaign on first-degree connections of targeted customers is 28% of the effect of the campaign on the targeted customers. By further leveraging the randomized experimental design we show that, consistent with a network externality account, the increase in activity among the non-targeted but connected customers is driven by the increase in communication between the targeted customers and their connections, making the local network of the non-targeted customers more valuable. Our findings suggest that in targeting CRM marketing campaigns, firms should consider not only the profitability of the targeted customer, but also the potential spillover of the campaign to non-targeted but connected customers.

Marketing Models for the Customer-Centric Firm

A customer-centric firm takes the view that there are three key drivers of (organic) growth and overall profitability: Customer acquisition , customer retention , and customer development (i.e., increasing the value of each existing customer (per unit of time) while they remain a customer). In this chapter we review the key data-based tools and methods that have been developed by marketing scientists (and researchers and practitioners in related fields such as operations research, statistics, and computer science) to assist firms in their understanding and implementing these activities more effectively.

Some Customers Would Rather Leave Without Saying Goodbye

We investigate the increasingly common business setting in which companies face the possibility of both observed and unobserved customer attrition (i.e., “overt” and “silent” churn) in the same pool of customers. This is the case for many online-based services where customers have the choice to stop interacting with the firm either by formally terminating the relationship (e.g., canceling their account) or by simply ignoring all communications coming from the firm. The standard contractual versus noncontractual categorization of customer–firm relationships does not apply in such hybrid settings, which means the standard models for analyzing customer attrition do not apply. We propose a hidden Markov model (HMM)-based framework to capture silent and overt churn. We apply our modeling framework to two different contexts—a daily deal website and a performing arts organization. In contrast to previous studies that have not separated the two types of churn, we find that overt churners in these hybrid settings ...