Research Topics:

Data Analysis

Content Type:

Glossary

Coefficient of Variation (CV) Definition

The ratio of the population (or sample) standard deviation to the population (or sample) mean.

The coefficient of variation, or CV, measures the relative variability of a data set's values as it relates to its mean. One example is the ratio of the population, or sample, to the standard deviation to the population, or sample, mean. CV is expressed as a percentage and is calculated by dividing the standard deviation of the data by the mean, then multiplying by 100. Essentially, CV helps researchers understand variability in data relative to its average. It helps distinguish random fluctuations from meaningful trends in data. What’s more, it identifies the variables that contribute most to variability. A low CV can indicate stability, while a high CV warns of potential areas of risk.

Who relies on the coefficient of variation (CV)?

CV helps marketing analysts, researchers and decision-makers assess the consistency and stability of a variety of marketing strategies, products and campaigns. By analyzing CV values, professionals can identify stable variables, thus allowing for more informed decisions about resource allocation and strategy.

Why should I care about the coefficient of variation (CV)?

CV provides insights into the reliability and predictability of marketing data. A higher CV indicates greater variability, which could mean certain factors are less stable and might need investigating. Conversely, lower CV values suggest more consistent performance.