International Peer-Reviewed JournalOpen AccessISSN 2456-8880
irejournals@gmail.com+91-7433024337

Home / Current Issue / Paper 1712215

1712215PublishedVol 9 · Issue 5

Customer Lifetime Value Prediction

Devansh Mishra Deepam Singh Dr. Ishrat Ali Prof. Sanjay Pachauri

Subject area: Science,Engineering and Technology  ·  Area of research: Data Science

DOI: https://doi.org/10.64388/IREV9I5-1712215

Abstract

In the contemporary business landscape, organizations are shifting from transactional metrics to a more relationship-oriented view of their customers. Central to this evolution is the concept of Customer Lifetime Value (CLV), a forward-looking prediction of the total net profit a business can expect from a customer over the entire duration of their relationship.4 Unlike metrics that measure past performance, predictive CLV uses data to forecast future value, empowering businesses to make proactive, data-informed decisions regarding marketing spend, customer acquisition, and retention strategies.6 The ability to accurately predict CLV allows a company to identify its most valuable customers, tailor its engagement strategies, and ultimately foster long-term, sustainable growth.

How to cite this paper

Devansh Mishra, Deepam Singh, Dr. Ishrat Ali, Prof. Sanjay Pachauri "Customer Lifetime Value Prediction" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 1833-1836 https://doi.org/10.64388/IREV9I5-1712215
Devansh Mishra, Deepam Singh, Dr. Ishrat Ali, Prof. Sanjay Pachauri "Customer Lifetime Value Prediction" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025, doi: https://doi.org/10.64388/IREV9I5-1712215
Devansh Mishra, Deepam Singh, Dr. Ishrat Ali, Prof. Sanjay Pachauri (2025). Customer Lifetime Value Prediction. Iconic Research And Engineering Journals, 9(5). doi: https://doi.org/10.64388/IREV9I5-1712215
Devansh Mishra, Deepam Singh, Dr. Ishrat Ali, Prof. Sanjay Pachauri "Customer Lifetime Value Prediction" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1712215
@article{1712215,
      author = {Devansh Mishra, Deepam Singh, Dr. Ishrat Ali, Prof. Sanjay Pachauri},
      title = {Customer Lifetime Value Prediction},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {5},
      pages = {1833-1836},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712215.pdf},
      abstract = {In the contemporary business landscape, organizations are shifting from transactional metrics to a more relationship-oriented view of their customers. Central to this evolution is the concept of Customer Lifetime Value (CLV), a forward-looking prediction of the total net profit a business can expect from a customer over the entire duration of their relationship.4 Unlike metrics that measure past performance, predictive CLV uses data to forecast future value, empowering businesses to make proactive, data-informed decisions regarding marketing spend, customer acquisition, and retention strategies.6 The ability to accurately predict CLV allows a company to identify its most valuable customers, tailor its engagement strategies, and ultimately foster long-term, sustainable growth.},
      month = {November},
      doi = {https://doi.org/10.64388/IREV9I5-1712215}
  }