Markov Chain Model
MODELING CUSTOMER RELATIONSHIPS
AS MARKOV CHAINS
Phillip E. Pfeifer
Robert L. Carraway f INTRODUCTION
The lifetime value of a customer is an important and useful concept in interactive marketing. Courtheaux (1986) illustrates its usefulness for a number of managerial problems—the most obvious if not the most important being the budgeting of marketing expenditures for customer acquisition. It can also be used to help allocate spending across media (mail vs. telephone vs. television), vehicles (list A vs. list B), and programs (free gift vs. special price), as well as to inform decisions with respect to retaining existing customers (see, e.g., Hughes, 1997). Jackson
(1996) even argues that its use helps firms to achieve a strategic competitive advantage.
Dwyer (1989) helped to popularize the lifetime value (LTV) concept by illustrating the calculation of LTV for both a customer retention and a customer migration situation. Customer retention refers to situations in which customers who are not retained are considered lost for good. In a customer retention situation, nonresponse signals the end of the firm’s relationship with the customer. In contrast, customer migration situations are those in which nonresponse does not necessarily signal the end of the relationship. Besides articulating this distinction between customer retention and migration, Dwyer listed several impediments to the use of LTV.
More recently, Berger and Nasr (1998) argue for the impor© 2000 John Wiley & Sons, Inc. and
Direct Marketing Educational Foundation, Inc. f JOURNAL OF INTERACTIVE MARKETING
VOLUME 14 / NUMBER 2 / SPRING 2000
43
PHILLIP E. PFEIFER AND
ROBERT L. CARRAWAY are with the Darden School of Business,
Charlottesville, Virginia.
JOURNAL OF INTERACTIVE MARKETING
between an individual customer and a marketing firm.
In addition to its flexibility, the MCM offers other advantages. Because it is a probabilistic model, it explicitly accounts for the
AS MARKOV CHAINS
Phillip E. Pfeifer
Robert L. Carraway f INTRODUCTION
The lifetime value of a customer is an important and useful concept in interactive marketing. Courtheaux (1986) illustrates its usefulness for a number of managerial problems—the most obvious if not the most important being the budgeting of marketing expenditures for customer acquisition. It can also be used to help allocate spending across media (mail vs. telephone vs. television), vehicles (list A vs. list B), and programs (free gift vs. special price), as well as to inform decisions with respect to retaining existing customers (see, e.g., Hughes, 1997). Jackson
(1996) even argues that its use helps firms to achieve a strategic competitive advantage.
Dwyer (1989) helped to popularize the lifetime value (LTV) concept by illustrating the calculation of LTV for both a customer retention and a customer migration situation. Customer retention refers to situations in which customers who are not retained are considered lost for good. In a customer retention situation, nonresponse signals the end of the firm’s relationship with the customer. In contrast, customer migration situations are those in which nonresponse does not necessarily signal the end of the relationship. Besides articulating this distinction between customer retention and migration, Dwyer listed several impediments to the use of LTV.
More recently, Berger and Nasr (1998) argue for the impor© 2000 John Wiley & Sons, Inc. and
Direct Marketing Educational Foundation, Inc. f JOURNAL OF INTERACTIVE MARKETING
VOLUME 14 / NUMBER 2 / SPRING 2000
43
PHILLIP E. PFEIFER AND
ROBERT L. CARRAWAY are with the Darden School of Business,
Charlottesville, Virginia.
JOURNAL OF INTERACTIVE MARKETING
between an individual customer and a marketing firm.
In addition to its flexibility, the MCM offers other advantages. Because it is a probabilistic model, it explicitly accounts for the
References: Berger, P.D., & Nasr, N.I. (1998). Customer Lifetime Value: Marketing Models and Applications Blattberg, R.C. (1998). Managing the Firm Using Lifetime-Customer Value Blattberg, R.C. (1987). Research Opportunities in Direct Marketing Blattberg, R., & Deighton, J. (1996). Manage Marketing by the Customer Equity Test Bronnenberg, B.J. (1998). Advertising Frequency Decisions in a Discrete Markov Process Under a Budget Constraint Courtheaux, R.J. (1986). Database Marketing: Developing a Profitable Mailing Plan. Catalog Age, June– July. Hillier, F.S., & Lieberman, G.J. (1986). Introduction to Operations Research (4th ed.) Hughes, A.M. (1997). Customer Retention: Integrating Lifetime Value into Marketing Strategies Jackson, B. (1985). Winning and Keeping Industrial Customers Jackson, D.R. (1996). Achieving Strategic Competitive Advantage Through the Application of the LongTerm Customer Value Concept Puterman, M.J. (1994). Markov Decision Processes: Discrete Stochastic Dynamic Programming. New York: John Wiley & Sons. White, D.J. (1993). A Survey of Applications of Markov Decision Processes the Operational Research Society, 44 (11), 1073– 1096.