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ArticleNew approach to customer segmentation based on changes in customer value

Monireh Hosseini2015

Article2015

New approach to customer segmentation based on changes in customer value

Monireh Hosseini · Mostafa Shabani

63 citations·0/0 files stored·Journal of Marketing Analytics

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Customer churn and segmentation Customer Service Quality and Loyalty Consumer Market Behavior and Pricing

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References

1999Building Data Mining Applications for CRM 2009Analytics at Work: Smarter Decisions, Better Results 2008Classifying the segmentation of customer value via RFM model and RS theory 2003An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry 1994Strategic database marketing 2004Integrating AHP and data mining for product recommendation based on customer lifetime value 2005Customer segmentation and strategy development based on customer lifetime value: A case study 2001Customer Relationship Management: An Analysis Framework and Implementation Strategies

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2023How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation 2020The practical approach in Customers segmentation by using the K-Means Algorithm 2021An analytical framework based on the recency, frequency, and monetary model and time series clustering techniques for dynamic segmentation 2017Statistics-based CRM approach via time series segmenting RFM on large scale data

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Year2015

Typearticle

Published2015-09-01

VenueJournal of Marketing Analytics

ISSN-L2050-3318

Languageen

Citations63

Files0 public / 0

ShelfCustomer churn and segmentation

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doi10.1057/jma.2015.10

openalex_workW2204903869

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2019

A new methodology for customer behavior analysis using time series clustering

2023A decade of marketing analytics and more to come: JMA insights

2022Multi-Behavior RFM Model Based on Improved SOM Neural Network Algorithm for Customer Segmentation

2023Customer Lifetime Value Prediction: Using Machine Learning to Forecast CLV and Enhance Customer Relationship Management