Multi-Campaign A/B Test
Find the highest-converting message, segment or tactic with a data-driven approach.
Multi-Campaign A/B Test is an OptiMonk feature that runs controlled experiments between two or more complete campaigns — or between a campaign and no campaign at all — splitting your visitor traffic across the test groups and measuring which produces the highest conversion rate and revenue impact. Unlike the standard within-campaign A/B test (which tests design variants, copy, and images within a single campaign), Multi-Campaign A/B Testing operates at a higher level: you select any existing campaigns from your account and pit them against each other as distinct test groups. This makes it possible to test questions that a within-campaign variant test cannot answer — whether gamification outperforms a standard list builder, whether a discount offer beats a free shipping bar, whether running multiple campaigns in sequence outperforms a single campaign, and whether running any campaign at all produces measurable revenue lift compared to a control group with no campaign. Up to five visitor groups can be configured per test, traffic is split at a percentage you define for each group, and results — impressions, conversions, and conversion rate — are tracked per group within the test's time window. Deeper metrics including average order value, number of orders, and attributed revenue are measurable through Google Analytics. Multi-Campaign A/B Tests run on a single domain, can only be run once, and must be ended manually.
Key benefits
- Test fundamentally different strategies, not just design details. Within-campaign A/B testing answers design questions — does this headline beat that one, does red convert better than green? Multi-Campaign A/B Testing answers strategy questions — does gamification beat a standard popup, does a campaign sequence outperform a single message, does targeting one audience segment outperform another? These are higher-stakes questions with larger potential revenue impact, and they require a framework that can hold entire campaign configurations in competition with each other — which Multi-Campaign A/B Testing is specifically built to do.
- Measure whether your campaigns produce revenue lift at all. One of the most valuable and underused test configurations is campaign versus no campaign — running an active campaign for 50% of visitors while the other 50% see nothing, and measuring the revenue difference. This is the only rigorous way to determine whether OptiMonk campaigns are producing net revenue gains or merely capturing conversions that would have happened anyway. Multi-Campaign A/B Testing makes this test straightforward: one group gets the campaign, one group is left empty, and the results show the actual revenue attribution with statistical confidence.
- Control traffic allocation to manage test risk. Not every test warrants a 50/50 split. If you are testing a new campaign strategy and want to protect the majority of your traffic from a potentially underperforming variant, you can allocate a smaller percentage — for example, 80% to your established campaign and 20% to the experimental one. This allows you to gather data on the new approach with limited exposure risk, then adjust the split as confidence in the new variant grows.
How it works
In OptiMonk, click New Campaign and select "Optimize a Website," then choose "Multi-Campaign A/B Test." This opens the A/B Test Center, where all previous tests are listed. Click New A/B Test, select the domain you want to run the test on (tests are per-domain), and give the test a descriptive name — including the domain and the subject of the test is recommended for easy identification later.
Click "Add campaign" for each group and browse your existing campaigns to assign one or more campaigns to it. Up to five visitor groups can be created, and each group can contain one or more campaigns. To test campaign versus no campaign, leave one group empty. Once all groups are configured, set the traffic percentage for each — the percentages must total 100%. Active campaigns added to the test are automatically paused as standalone campaigns and reactivated within the test framework when you start it.
Click Start to launch the test. While running, OptiMonk tracks impressions, conversions, and conversion rates per group and displays them on the test's page. Results reflect only the period during which the test ran — not all-time campaign data. For revenue and order data, connect the test to Google Analytics following the steps in OptiMonk's GA4 integration guide. When you have gathered sufficient data to make a decision, click End to stop the test. Tests can only be run once and cannot be restarted.
Frequently asked questions
What is Multi-Campaign A/B Test in OptiMonk?+
Multi-Campaign A/B Test is an OptiMonk feature that runs controlled experiments between two or more entire campaigns — or between a campaign and an empty control group — splitting visitor traffic across test groups at percentages you define. Unlike within-campaign variant testing, it tests complete campaign strategies against each other: different message types, different audience segments, different campaign combinations, or campaign versus no campaign. Results are tracked per group for the duration of the test, with deeper revenue data available via Google Analytics.
What is the difference between a Multi-Campaign A/B Test and a standard A/B test within a campaign?+
A standard within-campaign A/B test (Variant A/B test) tests different versions of the same campaign — swapping copy, images, colors, or CTAs — to find the highest-converting design within a consistent campaign concept. A Multi-Campaign A/B Test tests entirely different campaigns against each other — different message types, different templates, different targeting strategies, or different campaign combinations. Use variant testing to optimize a campaign you already believe is the right concept; use Multi-Campaign A/B Testing to decide which concept is right in the first place.
Can I test a campaign against a control group with no campaign?+
Yes — this is one of the most valuable Multi-Campaign A/B Test configurations. To run a campaign-versus-no-campaign test, add your campaign to one group and leave the other group completely empty. The empty group receives no OptiMonk campaigns during the test period. The results show the actual revenue lift produced by having the campaign versus not having it, which is the most rigorous way to establish the true revenue attribution of your OptiMonk campaigns.
How many campaigns and visitor groups can I include in one test?+
You can create up to five visitor groups in a single Multi-Campaign A/B Test. Each group can contain one or more campaigns. The test must run on a single domain — you cannot test campaigns from different domains in the same test. A given campaign can only be part of one active Multi-Campaign A/B Test at a time, and each test can only be run once and cannot be restarted after it ends.
What metrics does Multi-Campaign A/B Test track, and where can I see revenue data?+
The Multi-Campaign A/B Test results page shows impressions, conversions, and conversion rate per group for the duration of the test. For deeper revenue metrics — average order value, number of orders placed, and revenue attributed to each group — you need to connect OptiMonk to Google Analytics 4 and use the GA4 audience comparison feature to analyze the monetary performance of each test group. OptiMonk's documentation provides step-by-step instructions for this GA4 setup.
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