Cited by 159Customer churn and segmentationCustomer Service Quality and LoyaltyConsumer Market Behavior and Pricing

Investigating the role of product features in preventing customer churn, by using survival analysis and choice modeling: The case of financial services

Larivière, Bart, Van den Poel, Dirk·2004·Expert Systems with Applications

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Crossref · 10.1016/j.eswa.2004.02.002

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1 of 1 references verified0 citation errors · 0 not checkable

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  • Some studies measured the CAC and calculated it as the loss incurred when a customer churned.

    “Therefore, some studies measured the CAC, and calculated it as the loss incurred when a customer churned [8] [31] [72].”

    From A Survey on Churn Analysis in Various Business Domains (2020) · cites this paper as [8]

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Authors
Larivière, B., & Van den Poel, D.
Affiliations
Ghent University (BE)
Corresponding author
Larivière, Bart
Venue
Expert Systems with Applications
Publisher
Elsevier BV
Published
2004-08
Volume
27
Issue
2
Pages
277-285
ISSN
0957-4174 (ISSN-L)
OpenAlex
W2076313627
Cited by
159
References
1
Citations by year
2026: 2 · 2025: 6 · 2024: 7 · 2023: 2 · 2022: 7 · 2021: 9 · 2020: 7 · 2019: 4 · 2018: 3 · 2017: 2 · 2016: 6 · 2015: 7 · 2014: 7 · 2013: 8 · 2012: 12
FWCI
40.82
Type
journal article
Language
en
Open access
closed
Locations
  • Expert Systems with Applications (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Ghent University Academic Bibliography (Ghent University) (submittedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Marketing › Customer churn and segmentation
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
  • Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
Keywords
customer churn, customer retention, product attributes, financial services, cross-selling, consumer preferences, customer relationship management, survival analysis, hazard models, multinomial probit model

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