A/B testing is a method of comparing two or more versions of a campaign to determine which one performs better. Instead of guessing what works, you let real visitor data decide.
In OptiMonk, you can run A/B tests to optimize your popups, embedded content, and other on-site messages — helping you improve conversion rates, grow your email list faster, and increase revenue.
How does it work?
When you run an A/B test, your traffic is split between different versions of a campaign. Each version is shown to a separate group of visitors, and OptiMonk tracks key metrics (like conversion rate, sign-ups, or revenue) to identify the winner.
Once enough data is collected, you can confidently roll out the best-performing version to all your visitors.
Types of A/B Testing in OptiMonk
OptiMonk offers three types of A/B testing, each designed for a different use case:
1. Variant A/B Testing
This is the most common type of A/B test. You create multiple variants of the same campaign — for example, testing a different headline, image, offer, or CTA button — and OptiMonk splits traffic evenly between them.
Best for: Testing small changes within a single campaign, like copy tweaks, design changes, or different discount offers.
2. Multi-campaign A/B Testing
With multi-campaign A/B testing, you test entirely different campaigns against each other. This means you can compare completely different approaches — for example, a full-screen pop-up vs. a sidemessage, or a discount offer vs. a free shipping offer.
Best for: Testing different strategies, campaign types, or messaging approaches to find the overall best-performing tactic.
3. Split URL A/B Testing
Split URL testing lets you send visitors to different page URLs and measure which version drives better results. Instead of testing popup variations, you're testing entirely different landing pages or product pages.
Best for: Testing different page layouts, landing page designs, or completely different user experiences.
Why should you A/B test?
Make data-driven decisions — Stop guessing and let your visitors tell you what works.
Improve conversion rates — Even small improvements can have a big impact over time.
Reduce risk — Test changes on a portion of your traffic before rolling them out to everyone.
Learn about your audience — Every test teaches you something about what resonates with your visitors.
Tips for effective A/B testing
Test one thing at a time. If you change too many elements at once, you won't know which change made the difference.
Let your test run long enough. Don't call a winner too early — wait until you have statistically significant results.
Start with high-impact elements. Headlines, offers, and CTAs typically have the biggest influence on conversions.