If you’re considering a quantitative B2B research study, there are two key areas to keep in mind when determining sample size: desired reliability of the results and the budget. Obtaining a good sample can be a the single largest line item cost in a B2B marketing study.

The accepted reliability standard for quantitative research is 95% confidence level, with an accuracy of ±5%. This means that in 95 out of 100 repetitions of the survey, the results will not vary more than ± 5.0%. To achieve a 99% confidence level is highly impractical for most B2B marketers. The sample size needs to be almost doubled to achieve a 4% increase in confidence level.

The chart below provides information on the appropriate sample size for a given population at a 95% confidence level (assuming a 50%/50% maximum split on survey responses - " 50/50% proportion characteristic") with goal of ± 5% accuracy.

For example, when conducting a study on a known population size of 10,000, it would be necessary to conduct 400 randomly sampled surveys to achieve reliability results of ± 4.8% at the 95% confidence level.