Worse here than elsewhere. Headline tests win 3% of the time on landing pages, against 8% across all page types. The category is not the problem; this page is.
Layout tests carry a higher published rate on landing pages — 14% on 42 tests tests — though see the note below before reading that as a recommendation.
Small sample. Few of these tests cleared the bar. The 95% interval on that win rate runs 1% to 7%, so read the figure as directional.
| landing pages | all page types | |
|---|---|---|
| Tests analysed | 100+ | 500+ |
| Beat control | 3% | 8% |
| No measurable difference | 87% | — |
| Lost to control | 9% | — |
| Median lift when it won | not reported | — |
Median traffic per variant was 1060 visitors.
| change type | win rate on landing pages | tests |
|---|---|---|
| Layout | 14% | 42 tests |
| CTA copy | 10% | 31 tests |
| Styling | 7% | 50+ |
| Split URL | 6% | 250+ |
| Headline (this page) | 3% | 100+ |
Only change types with at least 30 tests on landing pages 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 | 42% |
| Lead / form submission | 19% |
| Signup / registration | 18% |
| Booking / appointment | 7% |
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.
The main heading is rewritten. Structure, styling and every other element stay put.
The headline changed from a duration-and-project-count message with a screenshot grid to a clickable-prototype-in-30-days message with a video play button and different body copy and call to action text.
The headline changed from a listicle promise of 5 success hacks to a subhead that cited a 92% statistic about early morning habits.
The hero headline and body changed from specific workflow and product naming to more generic template and product-page wording, the action label changed, and the purchase label became lifetime access.
The headline changed from a question about how successful people maintained masculinity and manhood after 40 to one paired with a subhead citing a 92% statistic about five crucial pre-6AM habits.
It changed the headline from pairing client results with practice growth to a two-line headline with supporting body copy about the device and a specialist CTA.
The centered generic headline was replaced with a left-aligned benefit-driven headline, a bullet list, category pills and focus-area buttons, and a product screenshot on the right.
It replaced the hero video with a background image, changed the hero headline and intro text, added a donation CTA button, and inserted key-stats and donation-progress sections after the hero.
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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