Life event-based marketing using AI

IF 10.5 1区 管理学 Q1 BUSINESS
Arno De Caigny, Kristof Coussement, Steven Hoornaert, Matthijs Meire
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引用次数: 0

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.
利用人工智能开展基于生活事件的营销
本文探讨了企业如何利用创新数据源和人工智能(AI)进行生命事件预测,从而更好地管理与客户的关系。在这项研究中,我们利用深度学习来探索将客户生成的文本数据纳入生命事件预测模型的附加值。此外,我们还提出了一个新框架,用于计算基于生命事件的营销活动的利润。我们在一个真实世界的数据集上对我们的研究问题进行了实证验证,该数据集包括金融服务业 21,898 名客户的 94,161 封电子邮件。首先,我们证明了生活事件对产品占有率和客户价值都有重大影响。其次,我们证明了文本数据能显著提高生活事件预测模型的预测性能。第三,我们计算基于生命事件的营销活动利润的框架表明,开展此类营销活动可以带来可观的投资回报,但需要一个性能卓越的生命事件预测模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
20.30
自引率
10.60%
发文量
956
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.
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