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Customer lifetime value: How to find the right calculation and prediction approach
Applied Marketing Analytics: The Peer-Reviewed Journal,
8
(1),
16-25
(2022)
Abstract
In this age of abundant data, there are special opportunities for companies to measure the value of their customers. Such analytical action can help inform business and marketing decisions. This article gives an overview of what is meant by customer lifetime value and describes four approaches to calculating its value. We compare the pros and cons of each approach and show how engaging with the measurement activity can be beneficial for your business. Finally, the article gives guidelines so that managers can decide which approach best fits their current situation.
Keywords: data science; statistical models; marketing decisions; data scientist; predictive modelling; machine learning; small business; SME
The full article is available to subscribers to the journal.
Author's Biography
Shirley Coleman is a business engagement statistician in the school of Maths, Statistics and Physics and a former President of the European Network of Business and Industrial Statistics. She is co-author (with Andrea Ahlemeyer-Stubbe) of ‘Monetising Data — How to Uplift Your Business’ and ‘A Practical Guide to Data Mining for Business and Industry’. Her focus is on data science applications and she works with small to medium enterprises (SMEs) in knowledge exchange partnerships.
Daniel Walker received an MSc in Mathematics and Statistics from Newcastle University in 2018. In 2020, he completed a two-year Knowledge Transfer Partnership (KTP) as an associate, where he worked closely with the company and Newcastle University. He engages with academic communities in a hosting capacity. His current role is Data Insight Manager for a north-east financial practice, helping SMEs realise value from their data.
Mohammed Rahman-Chowdhury is a Masters student in Mathematics and Statistics at Newcastle University.
Andrea Ahlemeyer-Stubbe is Director of Strategic Analytics at HackerAgency München GmbH and the author of ‘A Practical Guide to Data Mining for Business and Industry’ (Wiley). Upon receiving her Master’s degree in statistics from the University of Dortmund, Ms Ahlemeyer-Stubbe formed a consulting firm, offering customised professional services to her clients. She now leads HackerAgency Munich’s analytics team, drawing on the wealth of experience gained from her 20 years in the industry, specifically in the areas of data mining, data warehousing, database marketing, CRM, big data and social CRM. Ms Ahlemeyer-Stubbe is a frequent lecturer at several universities, as well as a speaker at professional conferences. She was President of European Network Business and Industrial Statistics (ENBIS) from 2007 to 2009 and is currently Co-chair of the Industrial Conference on Data Mining (ICDM).
Citation
Coleman, Shirley, Walker, Daniel, Rahman-Chowdhury, Mohammed and Ahlemeyer-Stubbe, Andrea (2022, June 1). Customer lifetime value: How to find the right calculation and prediction approach. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 8, Issue 1. https://doi.org/10.69554/TRUB4324.
© Henry Stewart
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Publications LLP