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Do split URL A/B tests work in Media & Publishing?

Weak on both counts. Split URL tests win 5% in Media & Publishing, below the 10% these tests manage across all industries and below the 12% that Media & Publishing manages across all change types. There is usually something better to spend a test slot on.

The strongest change type we can measure in Media & Publishing is Headline at 6% on 50+ tests.

Small winner set. Few of these tests cleared the bar. The 95% interval on that win rate runs 2% to 13%, so read the figure as directional.

The numbers

Won 5% No measurable change 77% Lost 19%
Media & Publishingall industries
Tests analysed50+1,000+
Beat control5%10%
No measurable difference77%
Lost to control19%
Median lift when it won not reported

Median traffic per variant was 899 visitors. Most ran on landing pages (32), content pages (23), homepages (3).

Every change type we can measure in Media & Publishing

change typewin rate in Media & Publishingtests
Headline 6%50+
Split URL (this page) 5%50+

What split URL tests in Media & Publishing 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
Purchase / order complete42%
Product or content page reached25%
Lead / form submission20%
Outbound click to a provider6%

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 Media & Publishing benchmarks; rates across all industries are on the split URL benchmark.

What counts as a split URL test

Traffic is split between two addresses. The variant is a different page at its own URL, not a modified version of the control.

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

Why there are no examples on this page

A split URL variant is a whole separate page, so every description of what changed reduces to "traffic goes to a different page". The detail lives on the variant page itself, which belongs to the customer.

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.