The Role of Within-Trip Dynamics and Shopper Purchase History on Unplanned Purchase Behavior

The recent surge in the importance of shopper marketing has led to an increased need to understand the drivers of unplanned purchases. This research addresses this issue by examining how elements of the current shopping trip (e.g., lagged unplanned purchase and cumulative purchases) and past purchases (e.g., average historical price paid by the shopper) determine unplanned versus planned purchases on the current trip. Using a grocery field study and frequent shopper data, we estimate competing models to test behavioral hypotheses using a hierarchical-Bayesian probit model with state dependence and serially correlated errors. Our results indicate that shoppers with smaller trip budgets tend to exhibit behavior consistent with a self-regulation model – an unplanned purchase decreases the probability of a subsequent unplanned purchase – but this effect reverses later in the trip. In contrast, shoppers with medium trip budgets tend to exhibit behavior consistent with a cueing theory model – an unplanned purchase increases the probability of a subsequent unplanned purchase – and this effect increases as the trip wears on. Further, factors from previous shopping trips predict unplanned purchases in the current trip, suggesting that retailers can use their frequent shopper program data to create customized shopping lists and improve the targeting of mobile app-based promotions.