Results 161 to 170 of about 4,363 (216)

Marketing-AutoM3L: domain-aware automated machine learning for financial customer analytics. [PDF]

Front Artif Intell
Tian Y, Shao W, Deng Z.
europepmc   +1 more source

The Significance of Relative Fat Mass in Chronic Obstructive Pulmonary Disease Prevalence and Severity: Evidences From Two Cohorts. [PDF]

Int J Chron Obstruct Pulmon Dis
Tu T, Yu Y, Fan Y, Li X, Ye Z, Xu R, Bu Y, Zhao X, Chen X, Liu C, Yu B, Xu Y, Zhang X, Huang Y.   +13 more
europepmc   +1 more source

A New Perspective on RFM Analysis

, 2017
The aim of this chapter is proposing a novel integrated Fuzzy Group Multiple Attribute Decision Making (FGMADM) and Fuzzy C-Means Clustering (FCM) as a DM tool for segmentation of customers (retailers), based on an updated RFM model. For this purpose, the most important criteria to evaluate retailers from the in depth literature survey and experts ...
Mohammad Hasan Aghdaie, Parham Fami Tafreshi   +1 more
openaire   +2 more sources

RECYCLING PROJECT WITH RFM ANALYSIS IN INDUSTRIAL MATERIAL SECTOR

, 2020
With the advancement of technology and the widespread use of the Internet, the concept of big data, which we are often beginning to hear its name, has emerged. Big data can be briefly defined as an unstructured data stack. It aims to transform the data collected from different sources into a meaningful and processable format.
ERPOLAT TAŞABAT, Semra, AKCA, Esra
openaire   +2 more sources

Customer Segmentation Using RFM Analysis: Real Case Application on a Fuel Company

, 2020
Abstract Customer segmentation is an important research area that helps organizations to improve their services according to customer needs. With the increased information that shows customer attitudes, it is much easier and also more necessary than before to analyze customer responses on different campaigns.
Ucal Sarı, İrem, Sergi, Duygu, Ozkan, Burcu   +2 more
openaire   +3 more sources

Group RFM analysis as a novel framework to discover better customer consumption behavior

Expert Systems with Applications, 2011
The RFM model provides an effective measure for customers' consumption behavior analysis, where three variables, namely, consumption interval, frequency, and money amount are used to quantify a customer's loyalty and contribution. Based on the RFM value, customers can be clustered into different groups and the group information is very useful in market
Hui-Chu Chang, Hsiao-Ping Tsai
openaire   +2 more sources

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Performance evaluation of different customer segmentation approaches based on RFM and demographics analysis

Kybernetes, 2016
Purpose The purpose of this paper is to determine the best approach to customer segmentation and to extrapolate associated rules for this based on recency, frequency and monetary (RFM) considerations as well as demographic factors. In this study, the impacts of RFM and demographic attributes have been challenged in order to enrich factors that
Peiman Alipour Sarvari, Alp Ustundag
exaly   +3 more sources

Customer Analysis Using the RFM Methodology in a Dental Clinic [PDF]

[The RFM methodology is based on three dimensions: Recency, which refers to the time elapsed since the patient's last visit; Frequency, which refers to the number of times the patient has visited the clinic; and Monetary value that refers to the amount of money that the patient has invested in the clinic.
Pillaca Castro, Abraham Moises, Pablo Felix, Melani Daniela   +1 more
openaire   +2 more sources