Category ratio: A search for an optimal solution to reduce choice overload

Abstract

AbstractThis paper endeavors to find an optimal solution to alleviate the harmful consequences of choice overload using assortment categorization. Past research on assortment categorization has primarily studied the type of category labels. Only a few studies focused on the number of category labels, and the extant research is inconclusive on the right number of labels. This paper argues that the number of options under each label is more important in reducing choice overload than the number of labels. We call the number of options under each label “category ratio”. We integrate the research from four streams to recommend an optimal range of category ratio. In a field and a lab experiment, we tested the optimal category ratio as an intervention in the reduction of choice overload. The results of both experiments found a significant reduction in choice overload for the optimal category ratio. In experiment 3, we manipulated the category ratio to test whether the optimal category ratio is better than the non‐optimal category ratio. The results of experiment 3 found that consumers experienced more satisfaction for the optimal category ratio than both uncategorized assortment and non‐optimal category ratio. Past research has found that fewer labels and uninformative categorization are not helpful in the choice process. This paper finds that a few labels are beneficial only when the category ratio is within the proposed optimal range. Uninformative labels also reduced choice overload when categorized using the optimal category ratio.