A/B Testing Display Ads: The 2026 Guide to Maximizing ROAS

Stop guessing if your new ad design is actually better. Enter your data below to instantly see if your A/B test results are statistically significant.

📊 Significance Calculator

Variation A (Control)



Variation B (Test)




How to Improve Your Test Results

If your test results aren’t significant, or you simply want to create a “Variation B” that beats your control, try changing these high-impact variables.

1. The Call to Action

The button is the most important part of the banner. Changing “Learn More” to “Get Offer” can double CTR.


Build a Better Button ➜

2. The Color Palette

Low contrast kills conversions. Use our palette generator to find colors that pop.


Generate High-Contrast Colors ➜

Frequently Asked Questions

What is Statistical Significance?

It is a mathematical way of proving that your results are real and not just luck. We use a 95% confidence interval, which means there is only a 5% chance the result was random.

How long should I run a test?

We recommend running a test for at least 7 days to account for weekends vs. weekdays, and until you have at least 1,000 impressions per variation.


Need Help Scaling Your Ads?

If you need to create hundreds of variations for testing, we recommend using automation tools.


Try Bannerwise for Automation ➜

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