A/B Testing & Experimentation in Webflow

Webflow's visual editor makes building beautiful websites accessible even without extensive coding knowledge. However, for A/B testing and experimentation, a bit of custom code comes in handy. Here's a short and clean example using Webflow's Interactions feature:

Scenario: Let's test two different call to action (CTA) buttons on a landing page to see which one converts better.

1. Define Variations:

• Create two separate divs (or any element) for each CTA variation.
• Give each div a unique identifier in the Webflow Designer (e.g., “cta-variation-1”, “cta-variation-2”).

2. Code the Experiment:

• Go to the Interactions panel in Webflow Designer.
• Click “Add New Interaction” and choose “Click” as the trigger.
• Set the element that triggers the interaction to be one of the CTA variations (e.g., “cta-variation-1”).
• In the “Actions” tab, add a “Run JavaScript” action.
• Paste the following code, replacing the variationId with the actual identifier of your variation:

JavaScript
// Get variation ID
const variationId = event.target.dataset.variationId;

// Send data to analytics tool (replace with your preferred method)
window.dataLayer.push({
  event: 'ctaClick',
  variationId,
});

// Show a success message or redirect based on variation (optional)
if (variationId === 'cta-variation-1') {
  // Show custom message for variation 1
} else if (variationId === 'cta-variation-2') {
  // Redirect to success page for variation 2
  window.location.href = '/success';
}

3. Repeat for the Second Variation:

• Create a new Interaction with the second CTA variation as the trigger.
• Replace the variationId in the JavaScript code with the identifier of the second variation.

4. Track Conversions:

• Use your preferred analytics tool (e.g., Google Analytics) to track clicks on each CTA variation and measure conversions.

Benefits:

• This approach is clean and maintainable, with minimal custom code.
• You can easily add more variations and track their performance.
• Webflow's visual editor makes setting up the experiment user-friendly.

Need Help?

Stuck with custom css code? Contact us.