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A/B testing benchmarks for Nonprofit

15% of A/B tests on Nonprofit sites beat their control. That is across 40 tests tested variants, ranking 4 of 11 industries we can measure.

Few of these tests cleared the bar. The 95% interval on that rate runs 7% to 29%, so read it as directional.

The numbers

Tested variants40 tests
Beat control15%
95% interval on that rate7% to 29%
Median lift when it won too few winners to report

What works in Nonprofit

No change type in Nonprofit reaches our 30-test minimum yet. Rates across all industries are on the change type benchmarks.

How we know these are Nonprofit sites

Industry is derived from the verified domain the Mida pixel actually fired on, not from what anyone told us at signup. That distinction matters: where we hold both, the self-reported industry and the verified one disagree 65% of the time. Domains the classifier could not place from their name were fetched and read directly, bringing coverage to 97.8% of tested variants.

Every industry we can measure

industrywin ratevariants
E-commerce 14%1,000+
SaaS / Software 9%500+
Professional Services 14%250+
Finance & Insurance 16%250+
Education 10%250+
Health & Wellness 15%250+
Media & Publishing 15%100+
Marketplace 12%100+
Travel & Hospitality 11%100+
Healthcare 8%100+
Nonprofit (this page) 15%40 tests

Who ran these tests

This is every Mida account that ran a readable test — in-house marketers, founders, product teams, and agencies working on client sites. Nothing here is filtered by who ran the experiment or how experienced they are.

Low win rates are normal in experimentation, including at the top end. Microsoft's experimentation team, reporting on its own platform, found that only about one third of ideas improve the metric they were designed to improve — and that roughly another third actively hurt it. That is a dedicated experimentation organisation with research, prioritisation and review behind every test.

A mixed population like this one runs below that. The gap is roughly what disciplined practice buys you: ideas grounded in research rather than opinion, one variable at a time, and tests built so the result can actually be read.

A win is a variant that beat its control on that test's primary goal with a statistically significant result. Tests that never got enough traffic to say anything either way are excluded. The methodology has the full detail, including what these numbers cannot tell you.