5.1 Introduction

The previous two chapters have discussed the integrated frameworks and key modeling issues with regard to customer acquisition and customer retention. In both cases the chapters looked at these two phenomena in the customer life cycle independently. Each chapter did this because it is critical to understand these phenomena in great depth to understand the drivers of the different aspects of customer acquisition and customer retention. However, it is myopic for a marketing manager to ignore the fact that these two processes are inherently linked together. All customers of a firm must first be acquired before effort can be placed on retention. And, eventually, all customers will churn from the firm at some point in time in the future. Ideally a firm wants to manage this process such that new customers are replacing those current customers who churn at an acquisition rate that is greater than or equal to the rate of churn. This way, the size of the customer base of the firm continues to grow (or at least does not shrink). In addition, once a customer is acquired the firm wants to build the relationship with the customer to extend the customer's life and profitability with the firm. Thus, a firm needs to ‘balance’ the marketing effort between acquisition and retention in order to maximize the profitability of the customer base over time.

There are often several key questions that need to be answered with regard to customer acquisition and retention (see Figure 5.1 for a graphical representation of the research issues in balancing customer acquisition and retention). Some of these questions are similar to those that were posed in the previous two chapters. However, we must still address these questions to be able to properly balance the marketing resources between these two parts of the customer life cycle. These questions include:

• What are the drivers of customer acquisition?
• How much do I need to spend in order to acquire a customer?
• Once I acquire a customer, how long can I expect that customer to be a customer?
• How much do I need to invest in the relationship in order to keep the customer longer into the future?
• Given my resource constraints, how much should I spend on acquisition efforts versus retention efforts to maximize long-term profitability?

There have been several research studies that have been conducted with the goal of trying to answer these key questions. Table 5.1 contains a representative set of studies that have considered these issues and accounted for many of the problems that might occur in the model-building process. To provide a comprehensive understanding of how to balance customer acquisition and retention, we will review the issues in the studies along with the related modeling techniques. We will also provide empirical examples at the end of chapter to demonstrate how to apply this knowledge to a representative sample of customers from a B2B firm.

Figure 5.1 Issues addressed in balancing acquisition and retention modeling.

Table 5.1 Review of customer acquisition and retention models.

Similar to customer acquisition and customer retention models, the first question that needs to be answered when considering model selection is whether the firm's customers purchase in a contractual versus non-contractual manner. In most instances this will determine the type of statistical model that needs to be used in order to gain any insights from the data.

5.1.1 Data for Empirical Examples

In this chapter we will be providing a description of the key modeling frameworks that attempt to answer each key research question raised at the beginning of the chapter. We will also be providing one empirical example at the end of the chapter which will show how sample data can be used to answer these key research questions. For all the empirical examples in this chapter we provide a dataset titled ‘Balancing Acquisition and Retention.’ In this dataset you will find one table of data which include a representative sample of 500 customers from a typical B2B firm, where all the customers are from the same cohort. In this case, the cohort consists of a random sample of 500 customers who all made their first purchase with the firm at the same time. We provide the transaction and firmographic information for each customer. Thus, the data table here consists of 500 customers × 14 variables (15 total columns).

The first data table (labeled Transactions) includes the following variables, which will be used in some combination for each of the subsequent analyses:

This data table will be used for the example presented at the end of this chapter. This example will cover models of customer acquisition, customer retention, and optimal resource allocation.