Leveraging Convert Web Testing and Liquid Templating for Dynamic Content Personalization in Shopify

THIS ARTICLE WILL HELP YOU:

• Dynamic Content Manipulation Using Liquid and JavaScript
• Example: Two-Version Content Toggle
• Direct Integration with Convert Experiments Variants
• Variant A CSS
• Variant B CSS
• Conclusion

Dynamic Content Manipulation Using Liquid and JavaScript

Shopify's Liquid templating engine offers a flexible way to build and customize your storefront. When combined with JavaScript, Liquid enables the rendering of multiple content versions, allowing for dynamic content manipulation based on user interactions or experiment variations.

Example: Two-Version Content Toggle

Consider a scenario where you want to test two different promotional banners (Version A and Version B) to see which one performs better in terms of user engagement. By using Liquid to render both versions and JavaScript to control which version is displayed, you can create a seamless A/B testing environment.

<!-- Version A Content -->
<div id="versionA" style="display: block;">
  
</div>

<!-- Version B Content, hidden by default -->
<div id="versionB" style="display: none;">
  
</div>

In this setup, the `toggleContent` function controls which version is displayed based on a parameter indicating the desired version. This mechanism can be tied to Convert Experiments by specifying which version to display for each experiment variant directly within the variant's setup.

Direct Integration with Convert Experiments Variants

When creating your variants in Convert Experiments, you'll inject CSS specific to each variant's desired outcome. For Variant A (showing Version A of the content), you'd add CSS to the Variation CSS editor to ensure Version A is visible. Similarly, for Variant B (to display Version B), you'd add a CSS to reveal Version B.

Variant A CSS

#versionA {
  display: block;
}
#versionB {
  display: none;
}

Variant B CSS

#versionA {
  display: none;
}
#versionB {
  display: block;
}

These CSS snippets are added directly to the CSS editors within the Visual Editor, ensuring that the correct content version is shown to users participating in each variant of the experiment.

Conclusion

Combining the flexibility of Shopify's Liquid templating language with the robust testing capabilities of Convert Experiments allows store owners to create highly personalized and dynamic user experiences. By methodically showing or hiding content based on user interactions or experiment outcomes, merchants can significantly improve engagement and conversion rates. This approach not only enhances the shopping experience but also provides valuable insights into user preferences, helping to inform future content and design decisions.