Research Topics:

Quantitative Research | Sampling | Telephone Interviewing/CATI

Content Type:

Glossary

Efficiency Definition

The degree to which the sample represents the population. See also precision.

Efficiency refers to how well a sample design produces precise and reliable estimates of population characteristics relative to the cost, time, or size of the sample. In sampling, efficiency is often measured in terms of precision – meaning the degree to which repeated samples would yield similar results (low variability, narrow confidence intervals).

For example, a simple random sample of 1,000 respondents might give a margin of error of ±3%. If a stratified random sample of 700 respondents gives the same margin of error (±3%), the stratified sample is said to be more efficient (equal precision with fewer cases). Some sampling methods (e.g., stratified, cluster, quota) can be more statistically efficient because they reduce variance without requiring larger, more expensive samples.

Who relies on efficiency?

In marketing research, researchers, clients and decision-makers all rely on efficiency. Researchers depend on efficient sampling and data collection methods to achieve precise results without wasting time or budget, while clients and executives count on that efficiency to ensure insights are delivered quickly, cost-effectively and with statistical reliability.

Why should I care about efficiency?

You should care about efficiency because it directly affects the quality and value of insights – an efficient sample design or data process provides the same (or better) level of precision with fewer resources, reducing costs and speeding up decision-making. In short, efficiency ensures that every dollar and every respondent in a study contributes maximum value, allowing organizations to make confident decisions while conserving time and money.