Estimate how many completed survey responses you may need for your market research project and understand what that number means for confidence, reliability and decision-making.
Designed for marketing teams, product teams, agencies, SMEs, charities and public sector organisations planning quantitative research projects.
Trusted by brands, agencies and public sector teams across multiple industries.
Your results
For a population of 100,000 at 95% confidence and 5% margin of error, aim for about 383 completed responses.
Assumes a random sample from the population.
MRFGR can help you design the survey, recruit the right participants and interpret the results.
The estimated invitations figure helps you understand how many people you may need to contact to achieve your target sample size.
The sample size estimate helps answer a practical question: do you have enough completed responses to make a reliable decision?
It gives you a statistical benchmark, but it does not guarantee useful insight on its own. The quality of the questionnaire, how the audience is recruited, how representative the sample is and how the results are interpreted all matter.
The completed sample shows how many usable survey responses you should aim for.
A well-targeted sample is often more valuable than a larger sample from the wrong audience.
Use the calculator above for a survey sample estimate. There is no single response range that suits every project. The audience, research question, sampling method and level of detail required all affect the number you need.
Quick directional customer survey
Brand, product or concept testing
Niche or hard-to-reach audience
Public sector / stakeholder survey
Tracking or segmentation study
This calculator does not set the number of interviews or focus groups you need. Qualitative research explores experiences and reasons in depth; agree the number and mix of participants around your research questions. Do not treat an interview count as a recommended survey sample.
A larger sample is not always better. A smaller, well-targeted sample can be more useful than a large sample of the wrong people.
MRFGR can help you decide what level of robustness is appropriate for your project.
Define clear research objectives
Use the best method for your goals
Analyse and act on the insight
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