What is an Ordinal Variable?
- Content Type:
- Glossary
Ordinal variable Definition
A variable which can be ordered from lowest to highest but the distance between the different order is not known. Letter grades given in school (A-F) would be one example.
An ordinal variable is a type of variable used in market research to represent data that can be ranked or ordered, but the intervals between ranks are not equal or known. For example, customer satisfaction levels (e.g., "very satisfied," "satisfied," "neutral") are ordinal variables.
Who relies on ordinal variables in the marketing research industry?
Market researchers, data analysts, survey designers and business strategists rely on ordinal variables to evaluate consumer preferences, satisfaction or attitudes in scenarios where order matters but precise differences between ranks are not required.
What are key aspects of ordinal variables in market research?
Key aspects include:
- Ranked data: Values indicate an order or hierarchy (e.g., first to last, best to worst).
- Unequal intervals: The distance between ranks is not consistent or meaningful.
- Descriptive nature: Provides insights into relative positions rather than exact measurements.
- Common usage: Frequently used in Likert scales, rankings and survey questions.
- Limited statistical operations: Allows for calculations like mode and median but not mean.
Why are ordinal variables important in market research?
Ordinal variables are important because they enable researchers to capture and analyze ordered preferences or attitudes without requiring precise numerical values. This makes them useful for understanding relative opinions and trends in consumer behavior.
How do market researchers use ordinal variables?
Market researchers use ordinal variables to assess customer satisfaction, rank product preferences or gauge levels of agreement or importance. For example, they might use a scale ranging from "strongly agree" to "strongly disagree" to measure consumer attitudes. These variables help researchers identify patterns and inform decisions about product development, marketing strategies and customer experience improvements.