One of the better bets in E-commerce. CTA copy tests win 20% there, against 12% for CTA copy tests across all industries and 10% for all change types within E-commerce. Ahead on both counts, which is the strongest signal this data offers — though see the note below on why these comparisons are not like-for-like.
It is the strongest change type we can currently measure in E-commerce.
| E-commerce | all industries | |
|---|---|---|
| Tests analysed | 50+ | 250+ |
| Beat control | 20% | 12% |
| No measurable difference | 56% | — |
| Lost to control | 24% | — |
| Median lift when it won | +54.2% | — |
Median traffic per variant was 3597 visitors. Most ran on homepages (32), product pages (22), other pages (15).
| change type | win rate in E-commerce | tests |
|---|---|---|
| CTA copy (this page) | 20% | 50+ |
| Layout | 11% | 100+ |
| Styling | 11% | 500+ |
| Split URL | 10% | 250+ |
| Social proof | 9% | 50+ |
| Price framing | 8% | 50+ |
| Hero image | 7% | 50+ |
| Headline | 7% | 100+ |
| Body copy | 6% | 100+ |
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 | 39% |
| On-page click / engagement | 35% |
| Add to cart | 9% |
| Subscription | 5% |
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 industry overview is at E-commerce benchmarks; rates across all industries are on the CTA copy benchmark.
The button's words change. Size, colour and position stay as they were. Change the colour too and you have two variables.
The add to cart button used a localized Danish call to action instead of the original label.
The mega menu CTA button text changed from "Shop" to "Order now".
It added a new view-item link next to the Add to Bag button on product cards and changed the cart button colors and layout.
It replaced the trial or catalog button text with a test-font label and started tracking click events.
The login and account labels and buttons were rewritten to promote a discount offer, the guest button was changed into a styled link, and the login pane was switched from stacked to side-by-side.
A new View options CTA button was added inside each product card on the collection page, linking to the product page.
The buy button text changed to a localized add-to-cart label, and its width, padding, and font size were adjusted for different screen sizes.
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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