Reducing the arbitrariness of a metric is distinct from the pursuit of validity, rational zero points, data transformations, standardization, and the types of statistical procedures one uses to analyze interval-level versus ordinal-level data. A variety of theoretical, methodological, and statistical tools can assist researchers who wish to make their metrics less arbitrary. These approaches can be combined with perspectives from classic test theory, item response theory, or other scaling models. The importance of considering arbitrary metrics for some applied areas of research is reemphasized.