Better here than elsewhere. Layout tests win 20% of the time on homepages, against 15% across all page types — 5 points better. If you are going to test layout anywhere, this is the page for it.
It is also the strongest change type we can measure on homepages — nothing else we track wins more often there.
| homepages | all page types | |
|---|---|---|
| Tests analysed | 100+ | 250+ |
| Beat control | 20% | 15% |
| No measurable difference | 71% | — |
| Lost to control | 9% | — |
| Median lift when it won | +29.5% | — |
Median traffic per variant was 2837 visitors.
| change type | win rate on homepages | tests |
|---|---|---|
| Layout (this page) | 20% | 100+ |
| Price framing | 16% | 49 tests |
| Hero image | 15% | 50+ |
| Split URL | 13% | 100+ |
| CTA copy | 11% | 100+ |
| Social proof | 10% | 50+ |
| Styling | 10% | 500+ |
| Headline | 8% | 250+ |
| Body copy | 8% | 100+ |
Only change types with at least 30 tests on homepages appear here.
A win rate only means as much as the thing being counted, so this is what these tests were actually optimising for.
| measured outcome | share of tests |
|---|---|
| Purchase / order complete | 43% |
| Signup / registration | 16% |
| On-page click / engagement | 14% |
| Lead / form submission | 8% |
Outcomes below 5% of the set are not listed, so these do not sum to 100. How the outcome was measured moves the win rate a lot — see the methodology.
These rates are not like-for-like. How often a test wins depends partly on what it chose to measure: a goal that records a soft signal — a click, a scroll — clears the bar more often than one that records a purchase. Across this data, tests measured against a proxy goal win 13%, against 9% for tests measured against a business outcome.
Categories differ a lot in that mix — proxy goals account for anywhere from 2% to 41% of a category's tests.
Hold the metric fixed and the spread narrows sharply. Comparing only tests measured against a business outcome, the gap between the highest and lowest category falls from 9 points to 6 — at which point the intervals overlap and the categories are not statistically distinguishable.
So read the table as a description of what happened, not as a ranking of what works. If you want the comparison to mean something, compare categories that were measured the same way. The methodology page has the full breakdown.
Blocks move, reorder or change position. No copy is rewritten and no new content is added. If you moved a section <em>and</em> rewrote it, that is two variables and the result will not tell you which one worked.
It replaced the native pricing, header, and footer sections with a custom two-card upsell block, with the add-unlimited option preselected and the CTA text and behavior rewritten.
The mobile navigation menu items had text only before, and then thumbnail images were added to them.
The main column reordered its content so the activity finder row appeared first instead of later on the page.
The first two navigation menu items were swapped in order in both the mobile and desktop nav bars.
The left-aligned headline and subhead with a hero image and CTA button were replaced by a centered, image-free headline with new copy, a centered CTA, and trust bullet points below.
The price element was moved above the title on product cards, and the spacing and position between the price and button were adjusted.
It added a toggle wrapper with two links for viewing all items or only in-stock parts, added a new mini-card, and hid the parts grid items until toggled.
These are individual tests, not rules. Each ran on one site, with one audience, against one page we are not showing you. They are picked to be illustrative rather than sampled at random, and a change that won here can lose on your page for reasons none of this captures. Read them as prompts for what to test, not as findings to copy.
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.
So treat these as a general base rate, not a target. If you would rather not close that gap the slow way, find a CRO agency in the United States, the United Kingdom, the Netherlands or Australia — or browse every region.
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.
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