Predictive analytics, the process of using current and/or historical data with a combination of statistical techniques to assess the likelihood of a certain event happening in the future, has become increasingly prevalent in interactive marketing. However, previous research on predictive analytics in interactive marketing has mostly assumed customers’ voluntary participation and engagement in predictive analytics, overlooking the role of customers’ psychological factors in driving customer engagement. Based on self-determination theory, this chapter provides a theoretical framework to understand customer engagement in predictive analytics. Specifically, this chapter proposes that predictive analytics positively influences customer engagement through need for meaningful affiliation, which is moderated by self-construal, and that predictive analytics negatively influences customer engagement through sense of control, which is moderated by data use transparency and trust. This chapter presents both theoretical contributions and practical implications to interactive marketing.
CITATION STYLE
Liu, M. W., Zhu, Q., Yuan, Y., & Wu, S. (2023). Applying Predictive Analytics in Interactive Marketing: How It Influences Customer Perception and Reaction? In The Palgrave Handbook of Interactive Marketing (pp. 667–682). Springer International Publishing. https://doi.org/10.1007/978-3-031-14961-0_29
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