Collective Response Spike Prediction for Mutually Interacting Consumers

Modeling how marketing actions in various channels influence or cause consumer purchase decisions is crucial for marketing decision-making. Marketing campaigns stimulate consumer awareness, interest and help drive interactions such as the browsing of product web pages, ultimately impacting an individual´s purchase decision. In addition, some successful campaigns stimulate word-of-mouth and social trends among consumers, and such collective behavior of consumers result in concurrent and correlated responses over a short term. Though each consumer´s response should be attributed with both the same individual´s experiences and the collective factors, unobservability of most word-of-mouth events makes the estimation challenging. The authors propose a new continuous-time predictive model for time-dependent response rates of each consumer, which can incorporate both the individual and the collective factors without explicit word-of-mouth observations. The individual factor is modeled as staircase functions associated with the experienced events by each consumer, and provides a clear psychological interpretation about how marketing advertising communications impact short-term and mid-term memories of consumers. The collective factor is modeled with aggregate response frequencies for mutually-interacting groups that are automatically estimated from data. The key idea to mine the mutually-interacting groups exists in a three-step estimator, which initially performs a Poisson regression without the collective factor, then does clustering of the residual time-series in the initial regression, and finally performs another Poisson regression involving the collective factor. The proposed collective factor robustly incorporates the underlying trends even when causality from one consumer´s event spikes to another consumer´s response is weak. High predictive accuracy of the proposed approach is empirically validated using real-world data provided by an online retailer in Europ- .