How Do I Set Up and Run a Variant A/B Test on OptiMonk?

Use a variant test to compare campaign versions, or a no-campaign control to compare a campaign with an unchanged experience. Choose the question before editing the popup: these test types answer different questions.

The setup below follows OptiMonk’s variant A/B testing guide, checked September 6, 2026. The planning worksheet and numerical example are editorial guidance, not customer results.

Choose the comparison

OptiMonk allows substantially different variants. Change one element when you need a focused explanation; if you test a whole redesign, describe the result as a comparison of complete versions.

Set up campaign variants

1. Open Campaigns and select the campaign.
2. Choose Add new variant to create at least two versions.
3. Open the variant by name to edit its design.
4. Review each version before activating it with its toggle.
5. Check the parent campaign’s status and display conditions before testing on your site.

The source says activating a new variant makes it available for A/B testing. Prepare your edits and measurement brief before switching it on, so an unfinished design does not become part of the test.

Add a no-campaign control when appropriate

On the campaign details page, OptiMonk documents Add A/B test version as the route to a control variant. The control appears without a design preview. For Experiences, the guide documents one control variant per Experience and a Test against control (no campaign) option.

A control helps answer a business-impact question only when the outcome can be measured for both groups. Popup form submissions alone are not a like-for-like sales measure for visitors who never see a popup.

Write a brief before launch

For example, an email-capture test might measure completed signups while also checking whether the offer interferes with checkout. Choose guardrails that fit your actual goal rather than copying a universal metric list.

Verify delivery before interpreting results

Preview the layouts on desktop and mobile. Check links, forms, confirmation and downstream lead delivery for each version. Confirm that the intended variants are active and that other campaigns are not unexpectedly overlapping the experience.

Record interruptions and material edits during the test. Changing the offer midway makes the before-and-after data harder to interpret as one stable comparison. Do not treat a dashboard status as proof that the experiment ran as planned.

Compare rates and uncertainty

An illustrative variant A with 30 signups from 1,000 measured exposures has a 3% rate. Variant B with 40 signups from 2,000 exposures has a 2% rate. B has more signups but a lower rate. These invented figures demonstrate denominator checking only; they do not establish statistical significance.

Do not declare a winner solely because one version leads early. Review sample size, uncertainty, measurement consistency and the decision rule you set. An inconclusive result is a valid outcome. The cited setup guide does not establish a universal minimum sample or a guaranteed lift for your campaign.

For status controls, see activating and pausing OptiMonk campaigns. For broader product evaluation, see the OptiMonk review.