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Optimising marketing strategies by customer segments and lifetime values, with A/B testing

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Every customer has different needs and purchasing behaviour. This paper shows how data science tools such as machine learning, artificial intelligence and A/B testing enable marketers to segment their target market, identify the most loyal high-value customers and their purchasing patterns, and calculate the lifetime value of these customer segments to optimise marketing strategies and campaigns. The paper also argues that A/B testing helps marketers make unbiased data-driven decisions, making it the gold standard for identifying the best marketing strategy.

Keywords: A/B testing; customer; experimentation; lifetime value (LTV); predictive analytics; segmentation

Document Type: Research Article

Affiliations: 1: Co-founder and Data Scientist, Axiomatic Data 2: Data Scientist, Facebook 3: Data Scientist, Vanguard Group

Publication date: 01 September 2021

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  • Applied Marketing Analytics is the major new professional journal publishing in-depth, peer-reviewed articles on all aspects of marketing analytics. Guided by an expert Editorial Board each quarterly 100-page issue - published both in print and online - features detailed, practical articles written by and for marketing analytics professionals on innovative thinking, strategies, techniques, software and applied research showing how major brands are collecting, interpreting and acting on marketing analytics, both around the world and across varied digital and non-digital marketing channels. Learn how to measure the effectiveness of your marketing initiatives more accurately, how this compares to your competitors, identify gaps in your marketing analytics program and what metrics that support sound marketing decision making - and add to the bottom line.
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