In line with both baselines. Price framing tests win 8% in E-commerce, against 11% for price framing tests generally and 10% for E-commerce generally. Neither the category nor the vertical is moving this much.
The strongest change type we can measure in E-commerce is CTA copy at 20% on 50+ tests.
Small winner set. Few of these tests cleared the bar. The 95% interval on that win rate runs 4% to 17%, so read the figure as directional.
| E-commerce | all industries | |
|---|---|---|
| Tests analysed | 50+ | 100+ |
| Beat control | 8% | 11% |
| No measurable difference | 81% | — |
| Lost to control | 11% | — |
| Median lift when it won | not reported | — |
Median traffic per variant was 1877 visitors. Most ran on product pages (37), homepages (25), category pages (8).
| change type | win rate in E-commerce | tests |
|---|---|---|
| CTA copy | 20% | 50+ |
| Layout | 11% | 100+ |
| Styling | 11% | 500+ |
| Split URL | 10% | 250+ |
| Social proof | 9% | 50+ |
| Price framing (this page) | 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 | 76% |
| Add to cart | 16% |
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 price framing benchmark.
The number stays the same; the presentation changes. Per-day instead of per-month, annual instead of monthly, fee broken out instead of rolled in, anchor shown or hidden.
It added a discount label showing how much was saved next to the sale price and changed the price box layout and sizes.
The base price was hidden, and the original price with a 10% discounted subscription price in strikethrough was added next to the purchase option labels, while the pack-size selector was moved into the add-to-cart aside.
The default price was hidden, and the one-time and subscription labels were updated to show prices, with the subscription option using a discounted price and struck-through original price.
The pricing list had one monthly rate shown twice, then a higher third tier was added.
It added a “Save X%” or “Save X” label next to the price and changed the price box layout and sizes.
A simple subscribe-and-save price box with bullet points was replaced by a best-value pricing panel that showed a crossed-out price, per-serving cost, subscription benefits, and a one-time purchase option with a button.
The plain product description and simple subscribe line were replaced with a highlighted subscription offer box that showed a price comparison, savings badge, benefit checklist, delivery frequency selector, and separate buy-once option.
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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