The recent surge in the importance of shopper marketing has led to an increased need to understand the drivers of unplanned purchases. The authors address this issue by examining how elements of the current shopping trip (e.g., lagged unplanned purchase, cumulative purchases) and previous shopping trips (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-program data, the authors estimate competing models to test behavioral hypotheses using a hierarchical Bayesian probit model with state dependence and serially correlated errors. The results indicate that shoppers with smaller trip budgets tend to exhibit behavior consistent with a self-regulation model (i.e., an unplanned purchase decreases the probability of a subsequent unplanned vs. planned purchase), but this effect reverses later in the trip. In contrast, shoppers with medium-sized trip budgets tend to exhibit behavior consistent with a cuing theory model (i.e., an unplanned purchase increases the probability of a subsequent unplanned vs. planned purchase), and this effect increases as the trip continues. The article concludes with a discussion of implications for research and practice.
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