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

Paromita Guha, Christina Echagarruga and Eva Qi Tian
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Paromita Guha: Co-founder and Data Scientist, Axiomatic Data, USA
Christina Echagarruga: Data Scientist, Facebook, USA
Eva Qi Tian: Data Scientist, Vanguard Group, USA

Applied Marketing Analytics: The Peer-Reviewed Journal, 2021, vol. 7, issue 2, 144-153

Abstract: 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: predictive analytics; customer; segmentation; lifetime value (LTV); experimentation; A/B testing (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:aza:ama000:y:2021:v:7:i:2:p:144-153

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