Predicting Customer Value Using Clumpiness: From RFM to RFMC
Published Online:1 Oct 2014https://doi.org/10.1287/mksc.2014.0873
References
- (2002) Bayesian neural network learning for repeat purchase modelling in direct marketing. Eur. J. Oper. Res. 138(1):191–211.Crossref, Google Scholar
- (2006) Twenty years of hot hand research: Review and critique. Psych. Sport Exercise 7(6):525–553.Crossref, Google Scholar
- (2004) Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management (Wiley, Indianapolis).Google Scholar
- (2008) Database Marketing: Analyzing and Managing Customers, Vol. 18 (Springer Verlag, New York).Crossref, Google Scholar
- (1998) A dynamic model of the duration of the customer’s relationship with a continuous service provider: The role of satisfaction. Marketing Sci. 17(1):45–65.Link, Google Scholar
- (2008) Database paper the IRI marketing data set. Marketing Sci. 27(4):745–748.Link, Google Scholar
- (2000) A benefit congruency framework of sales promotion effectiveness. J. Marketing 64(4): 65–81.Crossref, Google Scholar
- (2010) Competing on talent analytics. Harvard Bus. Rev. 88(10):52–58.Google Scholar
- (2004) Bowlers hot hands. Amer. Statistician 58(1):38–45.Crossref, Google Scholar
- (2013) Customer Centricity: Focus on the Right Customers for Strategic Advantage (Wharton Executive Essentials, Philadelphia).Google Scholar
- (2005) RFM and CLV: Using iso-value curves for customer base analysis. J. Marketing Res. 42(4):415–430.Crossref, Google Scholar
- (2010) Customer-base analysis in a discrete-time noncontractual setting. Marketing Sci. 29(6): 1086–1108.Link, Google Scholar
- (2003) Runs, regimes, and rationality: The hot hand strikes back. Working paper, Leeds School of Business, University of Colorado, Boulder.Google Scholar
- (1985) The hot hand in basketball: On the misperception of random sequences. Cognitive Psych. 17(3):295–314.Crossref, Google Scholar
- (2004) Valuing customers. J. Marketing Res. 41(11):7–18.Crossref, Google Scholar
- (2006) Modeling customer lifetime value. J. Service Res. 9(2):139–155.Crossref, Google Scholar
- (2006) The goal-gradient hypothesis resurrected: Purchase acceleration, illusionary goal progress, and customer retention. J. Marketing Res. 43(1):39–58.Crossref, Google Scholar
- (2006) CLV: A path to higher profitability. Technical report, Working paper, University of Connecticut, Storrs.Google Scholar
- (2008) Customer Lifetime Value: The Path to Profitability (Now Publishers, Boston).Google Scholar
- (2008) The power of CLV: Managing customer lifetime value at IBM. Marketing Sci. 27(4):585–599.Link, Google Scholar
- (2004) The determinants of pre- and postpromotion dips in sales of frequently purchased goods. J. Marketing Res. 41(3):339–350.Crossref, Google Scholar
- (2003) Scoring models. Kellogg on Integrated Marketing (John Wiley & Sons, Hoboken, NJ), 227–249.Google Scholar
- (2005) Can we predict customer lifetime value? J. Interactive Marketing 19(1):2–16.Crossref, Google Scholar
- (2000) Is the hot-hands phenomenon a misperception of random events? Japanese Psych. Res. 42(2):128–133.Crossref, Google Scholar
- (2008) A hidden Markov model of customer relationship dynamics. Marketing Sci. 27(2):185–204.Link, Google Scholar
- (2001) Data Mining Cookbook: Modeling Data for Marketing, Risk, and Customer Relationship Management (Wiley, New York).Google Scholar
- (1987) Counting your customers: Who are they and what will they do next? Management Sci. 33(1):1–24.Link, Google Scholar
- (2009) Portfolio dynamics for customers of a multiservice provider. Management Sci. 57(3): 471–486.Link, Google Scholar
- (2010) Planning to make unplanned purchases? The role of in-store slack in budget deviation. J. Consumer Res. 37(2):264–278.Crossref, Google Scholar
- (1989) The “hot hand”: Statistical reality or cognitive illusion? Chance 2(4):31–34.Google Scholar
- (2005) The cold facts about the “hot hand” in basketball. Anthology Statist. Sports 16:169.Crossref, Google Scholar
- (1999) Statistical tests for the hot-hand in basketball in a controlled setting. Amer. Statistician 1(1):1–20.Google Scholar
- (2013) New measures of clumpiness for incidence data. J. Appl. Statist. 40(11):2533–2548.Crossref, Google Scholar

