Museum visitor experience benchmark
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This calculator turns a museum's visitor feedback numbers into something you can defend in a board meeting: the response rate, the margin of error on your NPS and satisfaction scores, and whether the sample is large enough to compare exhibitions or months. It does not hand you an industry benchmark, because published museum benchmarks vary too much by country, museum type and channel to be a target; it shows you how to build your own.
How to use the benchmark calculator
Pick one period (a month or a year) and use it for every number. Enter visitors, responses collected, the promoter/passive/detractor counts from your 0–10 question, the number of satisfied answers from your satisfaction question, the number of exhibitions or zones you compare, and the languages and channels you offer. The defaults are an example.
The result updates as you type. Nothing is sent anywhere unless you e-mail yourself the report.
How it is calculated
NPS = % promoters (9–10) − % detractors (0–6). CSAT = satisfied answers ÷ all answers to the satisfaction question. Response rate = responses ÷ visitors.
Margin of error uses the conservative 95% formula 1.96 × √(0.25 ÷ n), with a finite-population correction when the sample is a large share of the visitors. The per-exhibition and per-month margins divide the responses evenly, which is optimistic; your busiest gallery will be better covered than this and your quietest worse.
The verdicts (“fine for comparisons”, “usable for trends”, “too wide to compare”) are rules of thumb at ±4 and ±7 points. A difference between two exhibitions smaller than the margin is noise.
What to do with the result
If the per-exhibition margin is too wide, collect more responses before changing anything: a kiosk at the exit of each gallery and a QR code in the gallery itself usually double the response count within a month. If the margin is fine, compare like with like, same question, same channel, same season, and set next season's target one margin of error above today's score.
The context on what museum visitor NPS and satisfaction typically look like, and why published figures differ, is in museum visitor NPS benchmarks. How museums collect feedback gallery by gallery, in the visitor's language, is on visitor experience measurement for museums.
Frequently asked questions
Why does the tool not give me an industry benchmark number?
Because published museum benchmarks are collected with different questions, channels and visitor mixes, and quoting one as a target would be misleading. The defensible benchmark is your own score, same question and channel, compared season to season and gallery to gallery.
How many responses does a museum need?
Enough that the margin of error per exhibition is smaller than the differences you want to act on. At 400 responses the margin is about ±5 points; at 100 it is about ±10. The calculator shows this for your numbers.
Should I use NPS or satisfaction for a museum?
Both, for different purposes. Satisfaction at the exit of each gallery tells you where to act this week; the recommend question (NPS) tells you about the overall visit and reputation. Keep each on its own channel and compare each with itself.
Do visitors in different languages answer differently?
Often, yes, because they are different audiences. That is a reason to offer the survey in their languages, not to compare their scores against each other without context.
Is my data stored?
No. The calculation runs in your browser. The e-mail report is sent once to the address you give.
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