Abstract
Accurately estimating consumers' willingness-to-pay (WTP) is crucial to product design, pricing decisions, and the design of competitive marketing strategies. However, traditional self-report measures of WTP are susceptible to many reporting biases, including tactical responding or an inability to make accurate estimates. Importantly, appraisals also occur automatically (i.e., in the absence of substantial time, intention, awareness, and/or substantial cognitive resources) and implicit measures used to capture automatic appraisals are less susceptible to the sort of reporting biases that self-report measures can be affected by. However, the only existing implicit measure for assessing automatic price appraisals (the Task Rule Congruency paradigm, 'TRC') is impractical because of the large number of trials and time it requires. Accordingly, here we introduce the Implicit Attribute Classification Task (IMPACT), test its effectiveness for the measurement of automatic price appraisals (Study 1), and directly compare its effectiveness and utility with that of the TRC (Study 2). We find that the IMPACT is an efficient measure of automatic price appraisals, that it produces considerably larger effects compared to the TRC, and that it does so while substantially shortening the procedure. We also discuss how the IMPACT scores can be used to derive an implicit measure of willingness to pay. Our findings make a substantial contribution to both research and practice by providing an effective tool that facilitates, for the first time, an efficient exploration of implicit WTP.