# 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](https://epyc.in/)? Contact us.