3 Organization of the Book

The book adopts a model-based approach toward CRM. It illustrates and reviews the quantitative and modeling aspects needed to understand and implement CRM strategies. The modeling techniques presented here form the foundation for designing and implementing strategic marketing decisions. A brief description of the chapters contained in this book is as follows:

• Chapter 1: Introduction. This chapter provides an overview and functioning of a CRM system. It introduces key concepts and metrics needed to understand and implement CRM models. It also describes the process of building and developing CRM models.
• Chapter 2: Need for CRM models. This chapter outlines the need for CRM models by emphasizing the developments thus far in the CRM literature. Further, this chapter discusses the overall structure of CRM models, and their uses and benefits from a business/marketing standpoint, rather than a technical one. The framework adopted in this book will be whether the models are deterministic or stochastic, and whether they are discrete or continuous. Thus all the models discussed in the book should fall into one of the five chapters that follow.
• Chapter 3: Models for customer acquisition. This chapter starts the discussion on the first stage of CRM – acquiring new customers. The objectives of customer acquisition modeling include identifying the right customers to acquire, predicting whether customers will respond to company promotion campaigns, forecasting the number of new customers, and examining the short- and long-run effects of marketing and other business variables on customer acquisition. The model specifications that are covered in this chapter include logit, probit, Tobit, linear regression, log-linear, vector autoregression, hazard function, and decision calculus. Besides covering the modeling aspects of customer acquisition, this chapter also reviews a large number of studies that focus on the effects of marketing variables as drivers or predictors of customer acquisition.
• Chapter 4: Models for customer retention. After customers have been acquired, this chapter talks about the second step of CRM – retaining customers. Customer retention strategies are used in both in contractual (where customers are bound by contracts such as cell (mobile) phone subscription or magazine subscription) and in non-contractual settings (where customers are not bound by contracts such as grocery purchases or apparel purchases). In providing the models for customer retention, the primary objectives of this chapter include examining the factors influencing customer retention, predicting customers' propensity to stay with the company or terminate the relationship, and predicting the duration of the customer–company relationship. In examining these factors on retention, this chapter reviews model specifications that include logit, probit, Tobit, multinomial logit, hazard function, discrete-hazard function, proportional hazards function, discrete proportional hazards function, random intercepts, Pareto/NBD, shifted-beta geometric distribution, log-normal, negative binomial, Poisson, linear regression, system of regressions, and deterministic methods.
• Chapter 5: Integrated models for acquiring and retaining customers. While most studies consider customer acquisition and retention as independent processes, only a few have linked them together. This chapter focuses on studies which seek to model the two processes simultaneously. Researchers have used several metrics in their studies, including acquisition spending per solicited prospect and the retention spending per customer, potential revenue streams for retention and acquisition, customers' probability to engage in a relationship and the duration of customers' relationship with the firm, and the time that elapses before a prospective customer acquires a particular service and the subsequent duration for which the customer retains service before dropping it. To understand the integrated approach to model acquisition and retention, this chapter reviews model specifications such as probit, Tobit, decision calculus, and simulation techniques. Therefore, the chapter focuses on models that help companies explore the optimal way of allocating resources on customer acquisition and retention, and the variables impacting the trade-off between customer acquisition and retention.
• Chapter 6: Models for customer churn. This chapter focuses on preventing customer churn, which is an important function in the CRM process of any firm. Specifically, the chapter describes customer churn models that focus on areas such as (a) modeling churn with time-varying covariates, (b) analyzing the mediation effects of customer status and partial defection on customer churn, (c) modeling churn using two cost-sensitive classifiers, (d) dynamic churn modeling using time-varying covariates, (e) factors inducing service switching, (f) antecedents of switching behavior, and (g) impact of price reductions on switching behavior. In understanding the above-mentioned topics in customer churn, this chapter reviews model specifications such as binomial logit, time-series regression, logistic regression, hierarchical logistic regression, hazard function, proportional hazards function, neural networks, decision trees, Markov models, and fuzzy logic.
• Chapter 7: Models for customer win-back. This chapter deals with the fourth component of CRM called customer win-back, reacquisition, reactivation, or regain – an area that lacks research interest. Specifically, the chapter will cover several models and topics that are applied in customer win-back such as (a) a conceptual approach for winning back customers, (b) adopting a lifetime value framework as a basis for customer win-back, (c) optimal pricing strategies for recapture of lost customers, and (d) a model for the perceived value of a win-back offer. The model specifications reviewed in this chapter include split-hazard function and ANOVA design.
• Chapter 8: Implementing CRM models. This chapter provides the implementation details about CRM models, as they apply to B2B and B2C companies. Specifically, the critical things required for an effective implementation of CRM models are data, technology enablement, a skilled workforce, and a relevant strategy to be followed based on the model outputs. This chapter also touches upon the financial benefits of building and implementing CRM models. Case studies highlighting the key factors for successful implementation are discussed.
• Chapter 9: The Future of CRM. This chapter discusses future directions with respect to quantitative model building and development. The chapter highlights emerging areas and topics such as social media, mobile marketing, and customized campaigns that are prime areas for future research. The popular commercial uses and expected future development trends are also identified for each of the three marketing methods. This chapter also highlights the gaps in current research and advocates areas in need of better models.