Numeric Forced Rank: A Lightweight Method for Comparison and Decision-making

Comparing products, features, brands, or ideas relative to one another is a common goal in user experience (UX) and market research. While Likert-type scales and ordinal stack ranks are often employed as prioritization methods, they are subject to several psychometric shortcomings. We introduce the numeric forced rank, a lightweight approach that overcomes some of the limitations of standard methods and allows researchers to collect absolute ratings, relative preferences, and subjective comments using a single scale. The approach is optimal for UX and market research, but is also easily employed as a structured decision-making exercise outside of consumer research. We describe how the numeric forced rank was used to determine the name of a new Google Cloud Platform (GCP) feature, present the findings, and make recommendations for future research.