Eva Ascarza

Article | Customer Needs and Solutions

In Pursuit of Enhanced Customer Retention Management: Review, Key Issues, and Future Directions

Eva Ascarza, Scott A. Neslin, Oded Netzer, Zachery Anderson, Peter S. Fader, Sunil Gupta, Bruce Hardie, Aurelie Lemmens, Barak Libai, David T. Neal, Foster Provost and Rom Schrift

In today’s turbulent business environment, customer retention presents a significant challenge for many service companies. Academics have generated a large body of research that addresses part of that challenge—with a particular focus on predicting customer churn. However, several other equally important aspects of managing retention have not received similar level of attention, leaving many managerial problems not completely solved, and a program of academic research not completely aligned with managerial needs. Therefore, our goal is to draw on previous research and current practice to provide insights on managing retention and identify areas for future research. This examination leads us to advocate a broad perspective on customer retention. We propose a definition that extends the concept beyond the traditional binary retain/not retain view of retention. We discuss a variety of metrics to measure and monitor retention. We present an integrated framework for managing retention that leverages emerging opportunities offered by new data sources and new methodologies such as machine learning. We highlight the importance of distinguishing between which customers are at risk and which should be targeted—as they are not necessarily the same customers. We identify trade-offs between reactive and proactive retention programs, between short- and long-term remedies, and between discrete campaigns and continuous processes for managing retention. We identify several areas of research where further investigation will significantly enhance retention management.

Keywords: customer retention; churn; customer relationship management; Customer Relationship Management; Measurement and Metrics;

Citation:

Ascarza, Eva, Scott A. Neslin, Oded Netzer, Zachery Anderson, Peter S. Fader, Sunil Gupta, Bruce Hardie, Aurelie Lemmens, Barak Libai, David T. Neal, Foster Provost, and Rom Schrift. "In Pursuit of Enhanced Customer Retention Management: Review, Key Issues, and Future Directions." Special Issue on 2016 Choice Symposium. Customer Needs and Solutions 5, nos. 1-2 (March 2018): 65–81. View Details

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Article | Journal of Marketing Research (JMR)

Retention Futility: Targeting High-Risk Customers Might Be Ineffective.

Eva Ascarza

Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models that identify customers at the highest risk of churning, no research has investigated whether it is indeed optimal to target those individuals. Combining two field experiments with machine learning techniques, the author demonstrates that customers identified as having the highest risk of churning are not necessarily the best targets for proactive churn programs. This finding is not only contrary to common wisdom but also suggests that retention programs are sometimes futile not because firms offer the wrong incentives but because they do not apply the right targeting rules. Accordingly, firms should focus their modeling efforts on identifying the observed heterogeneity in response to the intervention and to target customers on the basis of their sensitivity to the intervention, regardless of their risk of churning. This approach is empirically demonstrated to be significantly more effective than the standard practice of targeting customers with the highest risk of churning. More broadly, the author encourages firms and researchers using randomized trials (or A/B tests) to look beyond the average effect of interventions and leverage the observed heterogeneity in customers’ response to select customer targets.

Keywords: retention/churn; proactive churn management; Field Experiments; heterogeneous treatment effect; Machine learning; Customer Relationship Management; Risk Management;

Citation:

Ascarza, Eva. "Retention Futility: Targeting High-Risk Customers Might Be Ineffective." Journal of Marketing Research (JMR) 55, no. 1 (February 2018): 80–98. View Details

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Article | Marketing Science

Some Customers Would Rather Leave Without Saying Goodbye

Eva Ascarza, Oded Netzer and Bruce G.S. Hardie

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 tend to interact more, rather than less, with the firm prior to churning; that is, in settings where both types of churn are present, a high level of activity—such as customers actively opening emails received from the firm—is not necessarily a good indicator of future engagement; rather it is associated with higher risk of overt churn. We also identify a large number of “silent churners” in both empirical applications—customers who disengage with the company very early on, rarely exhibit any type of activity, and almost never churn overtly. Furthermore, we show how the two types of churners respond very differently to the firm’s communications, implying that a common retention strategy for proactive churn management is not appropriate in these hybrid settings.

Keywords: churn; retention; Attrition; customer base analysis; Hidden Markov Models; latent variable models; Customer Relationship Management; Consumer Behavior;

Citation:

Ascarza, Eva, Oded Netzer, and Bruce G.S. Hardie. "Some Customers Would Rather Leave Without Saying Goodbye." Marketing Science 37, no. 1 (January–February 2018): 54–77. View Details

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Article | Journal of Marketing Research (JMR)

Beyond the Target Customer: Social Effects in CRM Campaigns

Eva Ascarza, Peter Ebbes, Oded Netzer and Matthew Danielson

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.

Keywords: social effects; field experiment; mobile; Customer Relationship Management; Network Effects; Consumer Behavior;

Citation:

Ascarza, Eva, Peter Ebbes, Oded Netzer, and Matthew Danielson. "Beyond the Target Customer: Social Effects in CRM Campaigns." Journal of Marketing Research (JMR) 54, no. 3 (June 2017): 347–363. View Details

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Article | Journal of Marketing Research (JMR)

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

Eva Ascarza, Raghuram Iyengar and Martin Schleicher

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.

Keywords: churn/retention; field experiment; pricing; tariff/plan choice; targeting; Customer Relationship Management; Price; Performance Effectiveness;

Citation:

Ascarza, Eva, Raghuram Iyengar, and Martin Schleicher. "The Perils of Proactive Churn Prevention Using Plan Recommendations: Evidence from a Field Experiment." Journal of Marketing Research (JMR) 53, no. 1 (February 2016): 46–60. View Details

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Article | Marketing Science

A Joint Model of Usage and Churn in Contractual Settings

Eva Ascarza and Bruce G.S. Hardie

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).

Keywords: churn; retention; contractual settings; access services; Hidden Markov Models; RFM; latent variable models; Customer Value and Value Chain; Consumer Behavior;

Citation:

Ascarza, Eva, and Bruce G.S. Hardie. "A Joint Model of Usage and Churn in Contractual Settings." Marketing Science 32, no. 4 (July–August 2013): 570–590. View Details

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Article | Journal of Marketing Research (JMR)

When Talk Is "Free": The Effect of Tariff Structure on Usage Under Two- and Three-Part Tariffs

Eva Ascarza, Anja Lambrecht and Naufel Vilcassim

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.

Keywords: pricing; nonlinear pricing; discrete/continuous choice model; three-part tariffs; uncertainty; learning; free products; Price; Consumer Behavior; Analysis;

Citation:

Ascarza, Eva, Anja Lambrecht, and Naufel Vilcassim. When Talk Is "Free": The Effect of Tariff Structure on Usage Under Two- and Three-Part Tariffs. Journal of Marketing Research (JMR) 49, no. 6 (December 2012): 882–900. View Details

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Book Chapters

Chapter | Handbook of Marketing Decision Models | 2017

Marketing Models for the Customer-Centric Firm

Eva Ascarza, Peter S. Fader and Bruce G.S. Hardie

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.

Keywords: Customer Value and Value Chain; Customer Focus and Relationships;

Citation:
Ascarza, Eva, Peter S. Fader, and Bruce G.S. Hardie. "Marketing Models for the Customer-Centric Firm." In Handbook of Marketing Decision Models. 2nd ed. Edited by Berend Wierenga and Ralf van der Lans, 297–330. International Series in Operations Research & Management Science. Springer, 2017. View Details

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Cases and Teaching Materials

Case | 2015

EPILOGUE: Kate Spade New York: Will Expansion Deepen or Dilute the Brand?

Eva Ascarza and Keith Wilcox

Citation:
Ascarza, Eva, and Keith Wilcox. "EPILOGUE: Kate Spade New York: Will Expansion Deepen or Dilute the Brand?" Columbia CaseWorks Series. 2015. View Details

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Case | 2015

Kate Spade New York: Will Expansion Deepen or Dilute the Brand?

Keith Wilcox and Eva Ascarza

Citation:
Wilcox, Keith, and Eva Ascarza. "Kate Spade New York: Will Expansion Deepen or Dilute the Brand?" Columbia CaseWorks Series. 2015. View Details

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Working papers

Working Paper | HBS Working Paper Series | 2019

The Value of First Impressions: Leveraging Acquisition Data for Customer Management

Nicolas Padilla and Eva Ascarza

Managing customers effectively is crucial for firms' long-term profitability. By understanding differences across customers, firms can tailor their activities towards those customers for whom the intervention will pay off, therefore increasing the value of customers while maximizing the return on the marketing efforts. Targeting effectively ultimately depends on the firm's ability to precisely estimate differences across customers—a very difficult task when firms attempt to manage recently acquired customers for whom only the first purchase has been observed. We propose a model that allows marketers to form “first impressions" of customers right after having been acquired. We define a first impression as an inference (based on the observed behaviors at the moment of acquisition) that the firm makes about customers' traits that are relevant for the firm (e.g., whether the customer will purchase again, how s/he will respond to specific marketing actions). The main aspect of the model is that it captures latent dimensions that impact both the variety of behaviors collected at acquisition as well as future propensities to buy and to respond to marketing actions. Using probabilistic machine learning, we combine deep exponential families with the demand model, relating behaviors observed in the first purchase with consequent customer behavior. We first demonstrate that such a model is flexible enough to capture a wide range of heterogeneity structures (both linear and non-linear), thus being applicable to a variety of behaviors and contexts. We also demonstrate the model's ability to handle large amounts of data while overcoming commonly faced challenges such as data redundancy, missing data, and the presence of irrelevant information. We then apply the model to data from a retail context and illustrate how the focal firm could form customers' first impressions by merely using its transactional database. We show that the focal firm would significantly improve the return on their marketing actions if it targeted just-acquired customers based on their first impressions.

Keywords: Customer Management; targeting; Deep Exponential Families; Probabilistic Machine Learning; Customer Relationship Management; Customer Value and Value Chain; Consumer Behavior; Data and Data Sets; Mathematical Methods; Retail Industry;

Citation:
Padilla, Nicolas, and Eva Ascarza. "The Value of First Impressions: Leveraging Acquisition Data for Customer Management." Harvard Business School Working Paper, No. 19-091, February 2019. View Details

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