How many completed responses do you actually need? Set your confidence level and margin of error below.
Assumes the most conservative case (a 50/50 split on the question you care about most), so this is a safe upper bound — a real result skewed further from 50/50 needs fewer completes for the same margin of error.
Once you know your number, Wavefield fields the study and delivers weighted, significance-tested results — start a project.
95% is the standard choice for most market research and opinion polling — it's the industry default for a reason. Use 99% for high-stakes decisions where being wrong is costly, or 90% for a quick directional read where speed matters more than precision.
±5% is typical for general population studies. Tighter margins (±3% or better) are worth the extra sample for close races or high-stakes decisions — political horse-race polling usually wants ±3% or tighter. Looser margins (±7-10%) are fine for quick directional reads or hard-to-reach niche audiences where every extra complete is expensive.
For large or effectively unlimited populations (the general public, a broad consumer base), it barely changes the required sample at all. It matters more for small, finite audiences — e.g. surveying your own customer list of 800 people needs meaningfully fewer completes than an unlimited-population calculation would suggest.
No — a large but unrepresentative or low-quality sample can be worse than a smaller, well-screened one. Clean screeners, quota management, and speeder/straightliner detection matter as much as raw sample size. This calculator tells you the floor; data quality determines whether you can trust what you collect.
Comparing survey platforms? Wavefield vs. Qualtrics · Wavefield vs. SurveyMonkey · Read quota sampling vs. random sampling or what survey scripting involves
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