How can Artificial Intelligence (AI) be used to manage Customer Lifetime Value (CLV)—A systematic literature review

Edo Belva Firmansyah, Marcos R. Machado*, João Luiz Rebelo Moreira

*Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

2 Citations (Scopus)
54 Downloads (Pure)

Abstract

Customer Lifetime Value (CLV) represents the total worth of a customer to a company over time, aiding businesses in resource allocation and tailored marketing for profitability. This literature review fills a research gap by examining how customer risk factors are integrated into CLV calculations. We conducted a systematic literature review across databases, adhering to strict criteria for relevance and quality. The review analyzed CLV methodologies and outcomes, highlighting the use of mean–variance analysis to optimize customer portfolios, with customer income fluctuations identified as a major risk factor. The study also explores the evolution of CLV research, particularly in the application of Machine Learning (ML) for risk-adjusted CLV. Our findings offer a comprehensive overview, laying the groundwork for future research and helping businesses refine risk management strategies, identify high-risk customers, and enhance customer value through more dynamic, data-driven models.

Original languageEnglish
Article number100279
JournalInternational Journal of Information Management Data Insights
Volume4
Issue number2
DOIs
Publication statusPublished - Nov 2024

Keywords

  • UT-Hybrid-D
  • Information systems
  • Machine learning
  • Risk-Adjusted Revenue
  • Systematic literature review
  • Customer value

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