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A/B testing benchmarks

What actually wins, from thousands of real A/B tests run on Mida and concluded between August 2023 and August 2026. A win means the variant beat its control with a statistically significant result.

By what you change

change typewin ratetests
Layout 19%250+
Hero image 17%100+
Form 16%50+
CTA colour 16%32 tests
Styling 15%1,000+
Price framing 13%100+
CTA copy 12%250+
Body copy 11%250+
Split URL 11%1,000+
Headline 10%500+
Social proof 9%100+

By industry

industrywin ratevariants
E-commerce 14%1840
SaaS / Software 9%726
Professional Services 14%496
Finance & Insurance 16%428
Education 10%422
Health & Wellness 15%361
Media & Publishing 15%199
Marketplace 12%191
Travel & Hospitality 11%131
Healthcare 8%110
Nonprofit 15%40

Industry comes from the verified domain the Mida pixel fired on, covering 97.8% of tested variants — not from a self-reported field, which disagrees with it 65% of the time.

Read the method before the numbers

Most tests do not win, and most of what gets tested never moves anything. We exclude tests that never got enough traffic to say anything either way, because a flat result on too little traffic is not evidence a change failed. The methodology page states exactly what we exclude and what these numbers cannot tell you.

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.