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2017 | OriginalPaper | Chapter

4. Recency Frequency and Monetary Model

Author : David L. Olson

Published in: Descriptive Data Mining

Publisher: Springer Singapore

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Abstract

Recency, Frequency, and Monetary (RFM) analysis seeks to identify customers who are more likely to respond to new offers. While lift looks at the static measure of response to a particular campaign, RFM keeps track of customer transactions by time, by frequency, and by amount.

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previous chapter Market Basket Analysis
next chapter Association Rules
Literature
Miglautsch J (2002) Application of RFM principles: what to do with 1–1–1 customer? J Database Market 9(4):319–324
Olson DL, Chae B (2012) Direct marketing decision support through predictive customer response modeling. Decis Support Syst 54(1):443–451CrossRef
Olson DL, Cao Q, Gu C, Lee D-H (2009) Comparison of customer response models. Serv Bus 3(2):117–130CrossRef
Yang ZX (2004) How to develop new approaches to RFM segmentation. J Target Meas Anal Market 13(1):50–60CrossRef
Metadata
Title
Recency Frequency and Monetary Model
Author
David L. Olson
Copyright Year
2017
Publisher
Springer Singapore
Book
Descriptive Data Mining

Print ISBN: 978-981-10-3339-1

Electronic ISBN: 978-981-10-3340-7

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-3340-7_4

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