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Do styling A/B tests work in SaaS / Software?

Better than the SaaS / Software average, though not because the industry helps. Styling tests win 13% there against 9% for all change types in SaaS / Software. Across all industries styling tests run at 11%, so the category is carrying this, not the vertical.

It is the strongest change type we can currently measure in SaaS / Software.

The numbers

Won 13% No measurable change 76% Lost 11%
SaaS / Softwareall industries
Tests analysed100+1,000+
Beat control13%11%
No measurable difference76%
Lost to control11%
Median lift when it won +57.4%

Median traffic per variant was 1505 visitors. Most ran on homepages (78), pricing pages (16), lead capture pages (13).

Every change type we can measure in SaaS / Software

change typewin rate in SaaS / Softwaretests
Styling (this page) 13%100+
Split URL 12%100+
Body copy 9%33 tests
Headline 6%100+
CTA copy 2%50+

What styling tests in SaaS / Software measured

A win rate only means as much as the thing being counted, so this is what these tests were actually optimising for.

measured outcomeshare of tests
Signup / registration34%
Purchase / order complete19%
On-page click / engagement17%
Booking / appointment13%

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.

Why this table is not a ranking

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 SaaS / Software benchmarks; rates across all industries are on the styling benchmark.

What counts as a styling test

Visual treatment shifts — spacing, weight, borders, colour, shadows — with the same content in the same order. Move the content and it is a layout test. Rewrite it and it is a copy test.

Control and variant wireframe for a styling A/B test
Control on the left, variant on the right. Only the changed element is highlighted.

Styling tests that won in SaaS / Software

  • The navigation menu originally showed three links, and then the third link was hidden.

    Homepage+44.4%

  • The CTA link buttons changed between a blue background with white text and a white background with a blue border, while the text stayed the same.

    Homepage+42%

  • It hid a paragraph in the sixth div block and centered its text.

    Pricing page+72.9%

  • The CTA wrapper changed from a stacked layout to a side-by-side flex layout without changing any text.

    Product page+32.8%

Styling tests that did not

  • The old element was hidden and the new element was forced to show, while the wording stayed the same.

    HomepageNo significant difference

  • The page hid the element with id B instead of showing it.

    Landing pageNo significant difference

  • The hero form’s button kept the same text, while an animated rotating gradient border and glow was added behind it.

    HomepageNo significant difference

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.

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.