Survey Completion Rate Calculator

Enter survey counts

Fill what you know. Invitations and Target completes are optional.

Invitations sent (optional)

Used to compute response rate.

Surveys started

Respondents who began the survey.

Surveys completed

Respondents who reached the end.

Target completes (optional)

For planning required starts.

Confidence level 90% 95% 99%

Shown for completion rate only.

Calculate

Example data table

Formula used

• Completion rate = Completed ÷ Started
• Dropout count = Started − Completed
• Dropout rate = (Started − Completed) ÷ Started
• Response rate (optional) = Completed ÷ Invitations
• Completion confidence interval uses the Wilson score interval for a binomial proportion.

Tip: If your survey allows “partial completes,” treat them consistently (either as started-only or as completed) so trend lines stay comparable.

How to use this calculator

1. Enter Started and Completed counts from your survey platform.
2. (Optional) Add Invitations sent to compute response rate.
3. (Optional) Add a Target completes to estimate how many starts you need.
4. Pick a confidence level to view the completion rate interval.
5. Click Calculate. Use the download buttons to export results.

Why completion rate matters

Completion rate summarizes how well a questionnaire holds attention after a respondent starts. A low rate increases item nonresponse, raises cleaning effort, and can bias estimates if dropouts differ from finishers. Track completion alongside started counts to separate engagement problems from recruitment problems. Review it by device, language, quota cell, and traffic source, and watch for sudden breaks after content or logic changes.

Choosing the right denominator

This calculator defines completion as Completed divided by Started, which isolates the survey experience after entry. When invitations are available, Response rate equals Completed divided by Invitations and reflects reach. The overall yield can be viewed as Invitations × response rate, or Started × completion rate, depending on your workflow. Keep denominators consistent across waves; if you switch from “invited” to “started,” trends will shift even if respondent behavior stays stable.

Interpreting confidence bounds

A completion rate is a proportion, so sampling variability matters when started counts are small. The Wilson interval used here avoids overly narrow bounds near 0% or 100% and performs well for typical field sizes. Wider intervals signal uncertainty; avoid overreacting to week‑to‑week changes that remain inside the interval. If started is 80 and completed is 60, the point rate is 75%, but the interval will remind you the true rate may differ meaningfully.

Reducing dropouts with design

Dropouts equal Started minus Completed, and the dropout rate highlights friction. Shorten grids, move sensitive items later, and show progress feedback that matches actual remaining time. Test mobile layouts, reduce page load, and validate skip logic with real data paths. Add attention checks sparingly; too many can increase breakoff. Even a five‑point improvement can materially reduce the number of starts needed for a fixed completes target, which lowers panel costs and field time.

Reporting benchmarks and targets

For stakeholder reporting, pair completion with response rate, median duration, and breakoff locations. Include the confidence interval to communicate precision, especially for small subgroups. Set targets based on historical segments rather than overall averages, then use the target‑planning output to budget sample and oversample hard‑to‑reach groups. Document eligibility screens, partial‑complete rules, and bot filtering so comparisons remain defensible over time.

FAQs

What is survey completion rate?

Survey completion rate is the share of respondents who finish after starting. It is computed as completed surveys divided by started surveys, expressed as a percentage.

How is response rate different from completion rate?

Response rate reflects recruitment reach: completed surveys divided by invitations sent. Completion rate reflects experience after entry: completed divided by started. Both are useful, but they answer different operational questions.

Why does the calculator show a confidence interval?

The interval quantifies uncertainty around the completion proportion. The Wilson method stays reliable for small samples and for rates near the extremes, giving more realistic bounds than simple normal approximations.

What if my survey platform reports partial completes?

Choose a consistent rule. Treat partials as started-only if they did not reach the end, or count them as completed if your analysis accepts partials. Keep the same rule across time to preserve comparability.

How are target completes converted into required starts?

Required starts are estimated as ceiling(target completes ÷ current completion rate). If completion changes during fieldwork, rerun the calculator to update the starts estimate and avoid under‑recruiting.

How can I improve completion without hurting data quality?

Reduce length, simplify grids, optimize mobile flow, and fix confusing skip logic. Place sensitive items later, show accurate progress, and monitor breakoff points. Pilot changes and compare completion and interval shifts before full rollout.