The implementation of a CRM strategy is an ongoing process of developing and executing a series of small projects aimed at satisfying the business needs and enhancing the value proposition to customers. In this section, we focus on three essential ingredients needed to implement CRM strategies from a modeling perspective: database, technology, and metrics.
The database is the core of any CRM planning. Companies gather information to store, analyze, and make marketing decisions based on the results of data analysis. This section provides a basic overview of the categories of databases and the sources from which data can be collected.
There are several types of databases and various ways to categorize them. This can be done according to firms' main business function, information contents, underlying marketing activities, or database technology. As the focus of this book is on data modeling, we look at the following two types of databases in detail: the transaction-related database and the customer database.
Over a period of time, databases will begin to comprise prospects who have yet to be acquired, along with active and inactive customers. Information on prospects and active and inactive customers are useful to marketers and should be included in customer databases. While data from active customers help marketers learn what has been done well, data from inactive customers help marketers to identify what needs to be improved, and data from prospects who were not acquired show the effectiveness of acquisition efforts and the type of customer the firm has a hard time acquiring. For inactive customers, the following additional information would be important to document:
For prospects who were not acquired, the following information would be important to document:
Managers acquire databases from two main sources: primary data sources and secondary data sources. Figure 1.1 shows a concise summary of available data sources as primary and secondary data sources.
Primary data are original data collected firsthand by the focal firm that are not available or cannot be derived from any other sources. Primary data collection is usually conducted in-house in the forms of experiments or survey methods such as questionnaires, interviews, or observations. Although primary data collection is a costly and time-consuming process, it is sometimes necessary for managers to obtain primary data if the required data cannot be obtained elsewhere or if the reliability of those data cannot be determined even when they can be obtained from other sources.
On the other hand, secondary data are data that have already been made available or published in any form. There are two types of secondary data sources: internal records and external sources. Information from internal records is the primary information that the firm obtains directly from its daily business operations (e.g., sales results, cost information, etc.), from customer feedback, or from its marketing activities. This internal information usually comes from various departments within the firm, such as the internal marketing research department, sales analysis group, accounting department, or corporate strategic planning unit. Information from external sources is the secondary information obtained from non-internal sources. There are three main external sources:
The use of databases for collecting, storing, and analyzing customer data has been crucial for innovations in the CRM process. Nevertheless, technology improvements have been a key driver in making database innovations and other CRM processes accessible, user-friendly, and affordable for firms.
An important factor that drives CRM development in its current stage is the rapid growth of technology. CRM implementation thus has evolved into a user-friendly, flexible, low-cost, and high-tech process. In particular, the three main components of CRM technologies, namely, customer touch points, CRM applications, and data storage technology, have gone through significant improvements. Customer touch points have moved away from the traditional face-to-face interaction between customers and salespeople. With the introduction of Voice over Internet Protocol (VoIP) technology, speech recognition technology, and social networking applications, interactions with customers can be in various forms of Web-based (e-mail, web sites, Facebook, Twitter, etc.) and phone-based (telesales, automatic voice recognition systems, etc.) interactions rather than a physical interpersonal interaction. Further, with the widespread use of the Internet and the growth of PDAs and smart phones, CRM applications are now offered in many forms, such as traditional ERP (Enterprise Resource Planning) systems and mobile or Web-based online portals.
All these developments and enhancements have two key implications for CRM analysts in the area of modeling and data analysis. First, as more data become available, the ways of obtaining them have also increased tremendously. This has given rise to creative ways of collecting customer data and adding more data points about a particular customer, thereby creating a more complete picture of the customer. Second, while massive databases add to the knowledge and resource pool of the organization, they also pose significant modeling challenges regarding the use of appropriate data to glean relevant managerial insights.
The old adage ‘You cannot manage what you cannot measure’ is most appropriate where metrics are concerned. Metrics help companies track and assess their performance and, more importantly, evaluate the returns on their CRM initiatives. In the process of implementing CRM, managers have to deal with a huge amount of data with the ultimate goal of evaluating managerial performances based on the value that each individual customer brings to the firm. In order to record and quantify those evaluations, managers need a set of indicators that measure customer values. Metrics perform this role.
The benefits of developing and using metrics are significant to companies. Some of the key benefits that accrue to the firm are: (a) tighter control over business processes and CRM activities, (b) means to measure changes in revenues, costs, and profits, (c) benchmarks and targets to attain certain levels of performance, (d) measures on return on investment (ROI), (e) aid in the acquisition and retention, preventing churn, and assisting win-back of profitable customers, and (f) realigning marketing resources to maximize customer value.
There are two broad categories of metrics, brand-level and customer-level. Brand-level metrics are metrics that measure the brand's competitiveness in the market, such as market share, customer equity, sales growth, and so on. Customer-level metrics break down those brand-level metrics to the individual customer, such as acquisition cost per customer, size of wallet, and so on. When combined, brand-level and customer-level metrics give managers a complete picture of how the firm or the brand fares in the market, as well as how its customer needs differ on an individual level, and how to leverage these differences to enhance the overall competitiveness of the firm.
Table 1.1 presents some commonly used metrics at both brand-level and customer-level. At this stage, the table is meant to provide a general view of the types of CRM metrics available. In the subsequent chapters, we will delve further with detailed discussions about these metrics.
Metric | Definition | Use of metric |
1. Market share | The percentage of a firm's sales to the sales of all firms in a given market | Brand-level |
2. Sales growth | The increase or decrease in sales volume or sale value in a given period compared to that in the previous period | Brand-level |
3. Acquisition rate | The proportion of prospects converted to customers | Brand-level |
4. Acquisition cost | The acquisition spending of a focal firm per prospect acquired | Brand-level and customer-level |
5. Retention rate | The average likelihood that a customer makes a repurchase from the focal firm in period t, given that this customer has purchased in the last period t − 1 | Brand-level and customer-level |
6. Defection rate | The average likelihood that a customer defects from the focal firm in period t, given that this customer has purchased in the last period t − 1 | Brand-level and customer-level |
7. Survival rate | The ratio of customers who continue to remain as customers (survive) until a period t from the beginning of observing these customers | Brand-level |
8. Average lifetime duration | The average duration customers continue to remain as customers | Brand-level |
9. P-active | The probability of a customer making a repurchase (being active) in a given period | Customer-level |
10. Win-back rate | The ratio of acquisition of customers who had been lost in an earlier period | Brand-level |
11. Share-of-wallet | The ratio of total sales of all customers of the focal firm in a product category to the total spending of those customers in the product category across all different firms | Brand-level and customer-level |
12. Size of wallet | The total spending of a customer on a product category across all different firms | Customer-level |
13. Share of category requirement | The ratio of the sales volumes of a particular product category of the focal firm or brand to the total sales volumes of the product category in the market | Brand-level and customer-level |
Also considered the market share of a firm or a brand with respect to a particular product category | ||
14. Past customer value | The gross contribution of a customer when adjusted for the time value of money | Customer-level |
15. RFM value | RFM stands for Recency, Frequency, and Monetary value: | Customer-level |
– Recency indicates the most recent purchase date of a customer | ||
– Frequency measures how often a customer purchases from the firm | ||
– Monetary value measures the average per transaction spending of a customer | ||
16. Customer lifetime value | The total discounted contribution margins of a customer (excess of recurring revenues over recurring costs to the focal firm) over a specific time period | Customer-level |
17. Customer equity | The total lifetime value of all customers of the focal firm | Brand-level |
The important thing for a company to remember is that determining which metric(s) to measure and manage should depend on how each metric relates to the desired short-term or long-term outcome. If the metric(s) chosen cannot be quantifiably related to desired outcome measures such as profitability and shareholder value, the metric(s) are not generally worth measuring and managing.