Arno De Caigny, Kristof Coussement, Steven Hoornaert, Matthijs Meire
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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.
期刊介绍:
The Journal of Business Research aims to publish research that is rigorous, relevant, and potentially impactful. It examines a wide variety of business decision contexts, processes, and activities, developing insights that are meaningful for theory, practice, and/or society at large. The research is intended to generate meaningful debates in academia and practice, that are thought provoking and have the potential to make a difference to conceptual thinking and/or practice. The Journal is published for a broad range of stakeholders, including scholars, researchers, executives, and policy makers. It aids the application of its research to practical situations and theoretical findings to the reality of the business world as well as to society. The Journal is abstracted and indexed in several databases, including Social Sciences Citation Index, ANBAR, Current Contents, Management Contents, Management Literature in Brief, PsycINFO, Information Service, RePEc, Academic Journal Guide, ABI/Inform, INSPEC, etc.