Gain-probability diagrams in consumer research

Abstract

Marketing scholars often compare groups that occur naturally (e.g., socioeconomic status) or due to random assignment of participants to study conditions. These scholars often report group means, standard deviations, and effect sizes. Although such summary information can be helpful, it can misinform marketing practitioners’ decisions. To avoid this problem, scholars should also report the probability that one group’s member will score higher than another group’s member, and by various amounts. In this vein, newly conceived gain-probability diagrams can depict relevant, concise, and easy-to-comprehend probabilistic information. These diagrams’ nuanced perspective can contradict traditional significance test and effect size implications.