A/B Testing Widgets: What to Test and How to Interpret Results

Running widgets on your eCommerce store is a great way to engage customers, but guessing what works isn’t enough. That’s where A/B testing comes in.

With A/B testing, you can compare two variations of a widget to see which one drives more clicks or form submissions, and make data-backed decisions to improve performance.

This article walks you through what to test and how to read the results.

What Is A/B Testing?

In A/B testing (also called split testing), you create two versions of the same widget — for example:

• Version A: “Get 10% Off Your First Order”
• Version B: “Claim Your Welcome Discount”

Each version is shown to a portion of your visitors. The one that performs better (based on clicks or conversions) is the winner.

What You Can Test in a Widget

Here are the key elements that can make a difference — and can be safely tested without overlapping with your other metrics-focused efforts:

1. Headline Copy

Your headline is what visitors see first. Test short vs longer text, or different tones (urgent, friendly, benefit-driven).

Examples:

• “Get 10% Off Now” vs “Sign Up and Save Instantly”
• “Leaving so soon?” vs “One last thing before you go…”

2. Call-to-Action (CTA) Button Text

This is what the user clicks — small wording changes can boost action significantly.

Examples:

• “Get My Code” vs “Unlock Discount”
• “Join Now” vs “Send Me the Offer”

3. Trigger Type

Test how the widget appears — does it perform better with:

• Exit-intent (when they try to leave the page)?
• Time delay (after a few seconds)?
• Scroll trigger (after 50% of the page is viewed)?
  

One may work better on product pages, another on the cart.

4. Offer Type

You can test different offers to see what’s most motivating.

Examples:

• “10% Off” vs “Free shipping”
• “Win a gift card” vs “Get early access”

5. Design & Layout

Test a simple layout versus one with an image, icon, or badge. Small changes in design hierarchy can improve engagement.

How to Interpret the Results

Once your A/B test has run for a few days (or until you have enough views data), here’s how to make sense of the data:

Best Practices for A/B Testing Widgets

• Test one thing at a time (e.g., don’t change copy and design together)
• Run the test long enough to get meaningful data (usually a few hundred views per version)
• Apply what works across other widgets or campaigns
• Avoid testing on low-traffic pages where results may be too random

What Happens After the Test?

Once you have a clear winner:

• Replace the weaker version with the stronger one
• Use the insight in new widgets — e.g., if “Free Shipping” works better than “10% Off,” repeat that benefit elsewhere
• Continue testing — small improvements add up fast
  

Even if a test doesn't show a big difference, you're still learning what doesn’t need changing, and that’s just as valuable.

A/B testing takes the guesswork out of widget design. Start small, test often, and let your data do the decision-making.