Is Their Crystal Ball Cloudy or Clear? A Practical and Valid Measure of Consumers' Affective Forecasting Accuracy

Abstract

The inability to accurately predict our emotions has been implicated as the root of numerous problems in consumer well-being. For marketers, consumers' poor affective forecasting can drive the choice of ill-suited products, unreliable survey responses, or post-purchase dissatisfaction. But can marketers measure or improve the ability to make accurate affective forecasts? The present paper develops and validates a simple affective forecasting accuracy (AFA) scale that directly and reliably captures individual variation in consumers' ability to correctly forecast their future feelings. We show that this unidimensional measure has desirable psychometric properties, appropriate correlations and discriminability from related constructs, and reliably predicts consumers' ability to predict their affective responses to sporting event outcomes and special occasion experiences, above and beyond more cumbersome measures like emotional intelligence. Further, we demonstrate the effectiveness of a simple debiasing intervention (surrogate affective reports) in attenuating the affect forecasting errors of lower AFA consumers.