How Does A/B Split Testing Work?

Learn how to use A/B testing in V Bundles to optimize your bundle performance and increase conversions.

Published: January 4, 2026

The V Bundles A/B Split Testing feature allows merchants to compare different bundle variants and identify which versions resonate best with customers without requiring third-party tools.

Why A/B Testing Matters

A/B testing helps optimize store performance by enabling merchants to:

  • Compare different prices, layouts, or messaging strategies
  • Improve conversion rates through data-driven decisions
  • Understand customer preferences and behavior patterns

Over time, small refinements based on actual data can yield significantly better results.

How It Works Behind the Scenes

When A/B testing is enabled on a bundle:

  • All traffic to that bundle is automatically split evenly between the variants created
  • Each visitor sees only one variant, stored in their browser via a special session ID
  • The system uses cdmbn_session_id in local storage to track variant assignment

For Returning Visitors

  • Visitors using the same browser and device without clearing data will always see the same variant
  • Switching browsers, devices, or clearing local storage may result in a different variant assignment
  • Advanced users can manually reset this by accessing browser Developer Tools and deleting the cdmbn_session_id key

Setup Steps

  1. Open the Bundle – Access your bundle in the V Bundles app
  2. Enable A/B Testing – Click "Run A/B test" button
  3. Create Variants – Two default variants are provided; up to 4 total variants allowed per bundle
  4. Customize Each Variant – Set different deals, prices, titles, and images for each
  5. Publish – Launch the test to your store

What You Can and Cannot Test

Can Test:

  • Layout variations
  • Discount tiers
  • Product images
  • Button text and colors
  • Messaging and copy

Cannot Test:

  • Bundle visibility settings (markets, product selection)
  • Schedule (start/end dates)

Price Testing

Yes, you can test different prices as long as discounts are applied. However, the app cannot increase original product prices—to simulate increases, adjust the base product price and apply smaller discounts on specific variants.

Best Practices

  1. Test one variable at a time for clearer insights
  2. Run tests for at least 1-2 weeks to gather sufficient data
  3. Ensure adequate traffic before drawing conclusions
  4. Document your findings to inform future bundle strategies

Analyzing Results

The app provides built-in analytics showing:

  • Views per variant
  • Conversion rates
  • Revenue generated
  • Statistical significance

Use these metrics to determine the winning variant and apply those learnings to future bundles.

Need Help?

Contact our support team via live chat for guidance on setting up and interpreting your A/B tests.

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