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Survey sample size calculator

By the editors of Analytics1.comLast reviewed 19 October 2026

The short answer

For a large population, a survey needs about 385 completed responses for a 5% margin of error at 95% confidence. A small population needs fewer: from a list of 5,000 customers, about 357. Divide by your expected response rate to see how many people to invite.

On this page 6 sections
  1. Calculator
  2. The formula
  3. Choosing the inputs
  4. What sample size cannot fix
  5. Questions
  6. Sources

Survey sample size

For example, your customer list

50 is the safe default

Responses needed

357

Without population limit

385

People to invite

1,785

Leave the expected proportion at 50% unless you have a good prior estimate; it gives the most conservative sample size.

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The formula

The calculator uses Cochran's formula, n0 = z² x p x (1 - p) / e², where z is 1.645, 1.96 or 2.576 for 90, 95 or 99% confidence, p is the expected proportion and e the margin of error. For a known population N it applies the finite population correction, n = n0 / (1 + (n0 - 1) / N).

Choosing the inputs

  • Margin of error: 5% is common for customer surveys; 3% for decisions where a few points matter.
  • Confidence level: 95% is the usual default.
  • Expected proportion: 50% gives the largest, safest sample. Use a lower figure only if you have good evidence, for example from a previous survey.
  • Response rate: be realistic. Email surveys to customers often get well under 30%; in-product surveys more.

What sample size cannot fix

The margin of error only covers random sampling error. If the people who answer differ from those who do not (the happiest and angriest customers reply most), a bigger sample just measures the bias more precisely. Send the survey to a random or complete list, keep it short, and send one reminder.

Analysing an NPS survey? The NPS calculator shows the margin of error for the score itself, which is wider than for a simple percentage.

Questions

How many survey responses do I need?
About 385 for a 5% margin of error at 95% confidence when the population is large. For a population of 1,000 it falls to about 278, and for 500 to about 218.
Does a bigger population need a much bigger sample?
No. Above a few tens of thousands, the required sample barely changes: about 385 responses give a 5% margin at 95% confidence whether the population is 50,000 or 50 million.

Sources

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