Unveiling the web of interactions: Analyzing dynamic customer engagements across multiple websites

Abstract

Online customers exhibit unique dynamic patterns during their journey. In the early phases, customers gather different information from multiple websites. Collectively, the information serves as references, helping customers to make informed decisions. Further, inferior options are eliminated until the journey converges on a single website for conversion. In this study, we examine the dynamic interactions among online customers and websites. To capture the dynamics, we propose a metric, momentum of information-building and incorporate the measure into a dynamically and mutually exciting marked point process model. We apply the proposed model to clickstream data for hotel bookings and find strong evidence of dynamic behavior. Also, we show that ignoring the dynamics may lead to bias in estimating the carryover and spillover effects and diminish the prediction accuracy of website visits and conversions. Furthermore, we offer recommendations for effective advertising strategies focusing on key aspects such as advertising density, timing, and targeting.