Results 161 to 170 of about 29,488 (189)

Predicting customer value per product: From RFM to RFM/P

Journal of Business Research, 2021
Abstract Recency, frequency, and monetary (RFM) models are widely used to estimate customer value. However, they are based on the customer perspective and do not take the product perspective into account. Furthermore, predictability decreases when recency, frequency, and monetary values vary among product categories.
Rodrigo Heldt, Cleo Schmitt Silveira, Fernando Bins Luce   +2 more
openaire   +1 more source

A stochastic RFM model

Journal of Interactive Marketing, 1999
Abstract A central problem in database marketing is how to choose which customers in the firm's database to target with an offer. This paper presents a simple stochastic RFM model to carry out such a task. By making a few straightforward assumptions about the customers in the database, the stochastic model provides a means of (1) ranking customers in
Richard Colombo, Weina Jiang
openaire   +1 more source

Customer clustering using RFM analysis

2018 26th Signal Processing and Communications Applications Conference (SIU), 2018
In this study, customers' behaviors are determined by detecting natural clusterings using existing reservation and customer data. We also customize their services and sales strategies according to these behaviors. The basic characteristics that provide these existing heuristics have been extracted by the decision tree approach after the K-means is ...
Muhammet Pakyürek, Mehmet Selman Sezgin, Sedat Kestepe, Büşra Bora, Remzi Düzağaç, Olcay Taner Yıldız   +5 more
openaire   +1 more source

RFM Variables Revisited Using Quantile Regression

2011 IEEE 11th International Conference on Data Mining Workshops, 2011
We revisit well-known variables for database marketing/CRM and relationship marketing using a new methodology: Binary Bayesian Quantile regression. This method allows for a more thorough investigation of the relationship between the response variable and the covariates.
Michel Ballings, Dries Benoit, Dirk Van den Poel   +2 more
openaire   +1 more source

Vollstochastische RFM-Prognosemodelle

2013
Vollstochastische Modelle basieren auf den Annahmen des stochastischen Prozesses. Sie beschranken sich auf das Identifizieren des „Wahrscheinlichkeitsgesetzes“, nach welchem beobachtbare Transaktionen sich nachempfinden lassen.
openaire   +1 more source

TEACHING STATISTICAL RFM SEGMENTATION IN EXCEL

INTED Proceedings, 2018
RFM (Recency, Frequency, Monetary) segmentation, visualization and interpretation belong among essential skills expected from "business study programs" graduates. However, specialized SWs suitable for these analyses aren’t usually available at universities.
Maria Králová, Pavel Lasak
openaire   +1 more source

Toward Targeted Mining of RFM Patterns

IEEE Transactions on Neural Networks and Learning Systems
In today's era of information overload, leveraging data mining techniques to understand and analyze customer behavior has become essential for businesses. Among these techniques, the recency, frequency, and monetary value analysis model serves as a powerful tool for customer segmentation, enabling companies to identify high-value customers.
Xiaoye Chen, Wensheng Gan, Zefeng Chen, Jian Zhu, Ruichu Cai, Philip S. Yu   +5 more
openaire   +2 more sources

Knowledge Discovery on RFM Model using Bernoulli Sequence

SSRN Electronic Journal, 2009
The objective of this paper is to introduce a comprehensive methodology to discover the knowledge for selecting targets for direct marketing from a database. This study expanded RFM model by including two parameters, time since first purchase and churn probability.
I-Cheng Yeh, King-Jang Yang, Tao-Ming Ting   +2 more
openaire   +1 more source

RFM segmentation and customer churn

2019
Since the increased importance is placed on consumer's purchasing behavior, more and more firms are focusing on customer segmentation to get insights about their clients. RFM segmentation is becoming, increasingly, popular in businesses as a marketing tool, which is used to group clients based on three fundamental features; the time elapsed from the ...
openaire   +1 more source

RFM approach for telecom insolvency modeling

Kybernetes, 2016
Purpose – The purpose of this paper is to present application of recency, frequency and monetary value (RFM) approach to predict customer insolvency using telecommunication data corresponding to RFM of late payments. The study tackles a serious problem that telecommunication companies often face and shows the ways to ...
openaire   +1 more source