What is a characteristic of ordinal categorical data?

Ordinal categorical data is distinguished by the fact that its values can be ranked or ordered based on a specific criterion. For example, when assessing customer satisfaction, responses may be categorized as "poor," "average," and "excellent." These categories have a clear hierarchy, where "excellent" is understood to represent a higher level of satisfaction than "average," and "average" is higher than "poor."

This ranking characteristic is what separates ordinal data from nominal categorical data, where values are merely labels without an inherent order. Unlike numerical data, ordinal categorical data does not involve quantitative measurements; thus, options suggesting values must be numerical or only non-numeric do not accurately reflect the nature of ordinal categorical data. Randomness isn't a defining feature of ordinal data either; rather, there should be a systematic way to rank the categories.