Peak-End rule versus average utility: How utility aggregation affects evaluations of experiences

The “Peak-End rule” which averages only the most extreme (Peak) and the final (End) impressions, is often a better predictor of overall evaluations of experiences than average impressions. We investigate the similarity between the evaluations of experiences based on Peak-End and average impressions. We show that the use of the Peak-End rule in cross-experience comparisons can be compatible with preferences for experiences that are better on average. Two conditions are shown to make rankings of experiences similar regardless of the aggregation rule: (i) the individual heterogeneity in the perception of stimuli, and (ii) the persistence in impressions. We describe their effects theoretically, and obtain empirical estimates using data from previous research. Higher estimates are shown to increase correlational measures of association between the Peak-End and average impressions. The high association per se is shown to be not only a theoretical possibility, but an empirical fact.