Life event-based marketing using AI

Arno De Caigny, Kristof Coussement, Steven Hoornaert and Matthijs Meire

Journal of Business Research, 2025, vol. 193, issue C

Abstract: This paper investigates how firms can leverage innovative data sources and Artificial Intelligence (AI) for life event prediction to better manage the relationship with their customers. In this study, we leverage deep learning to explore the added value of incorporating textual customer-generated data in life event prediction models. Furthermore, we propose a new framework to calculate the profit of life event based-marketing campaigns. We empirically validate our research questions on a real-world dataset including 94,161 email messages of 21,898 customers in the financial services industry. First, we show that life events have a significant impact on both product possession and customer value. Second, we demonstrate that textual data significantly boosts the predictive performance of life event prediction models. Third, our framework to calculate profit for life event-based marketing campaigns shows that running such campaigns can lead to a substantial return on investment but requires a performant life event prediction model.

Keywords: Business analytics; Life event prediction; Predictive analytics; Deep learning; Text analytics, customer relationship management (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:193:y:2025:i:c:s0148296325001729

DOI: 10.1016/j.jbusres.2025.115349

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