International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 6 Issue 6
November-December 2024

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Calculating Customer Lifetime Value through Data Analysis

Author(s) Akash Pant
Country India
Abstract Customer Lifetime Value (CLV) is a crucial metric for businesses to understand the long-term value of their customers. This research paper delves into the significance of CLV, explores various methods for calculating it through data analysis, and discusses the implications of accurate CLV estimation on business strategies. By leveraging data analytics techniques, businesses can gain valuable insights into customer behaviour, preferences, and profitability, ultimately leading to improved decision-making and enhanced customer relationships.
Customer Lifetime Value (CLV) is a vital metric for businesses to comprehend the long-term value of their customers. The research paper highlights several key points regarding CLV:
Calculation Factors: CLV calculations should consider indirect costs like administrative, marketing, and legal costs, not just direct expenses.
Limitations: CLV based solely on spending may not fully represent a customer's value, as factors like brand advocacy, referrals, and feedback also contribute.
Historical Data: CLV is often calculated using past customer data, which may not accurately predict future customer behaviours due to changing trends and customer preferences.
Pareto's Principle: This principle, known as the 80/20 rule, can be applied to CLV to identify high-value customers and key factors influencing CLV.
Overall, the paper emphasizes the importance of understanding CLV beyond mere spending, considering historical data limitations, and utilizing tools like Pareto's Principle to optimize customer value and business strategies.
Keywords Customer Lifetime Value, Data Analysis, Customer Behaviour, Business Strategies, Data Analytics
Field Business Administration
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-04-12
Cite This Calculating Customer Lifetime Value through Data Analysis - Akash Pant - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.16478
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.16478
Short DOI https://doi.org/gtqx2f
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 6 Isu 6Cover Page Vol 6 Isu 5Cover Page Vol 6 Isu 4

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9898-5948-55 editor@ijfmr.com