Current Page

Current Page

Current Page

Feb 5, 2025

How to Analyze A/B Test Results in LogRocket with Optimal UX Integration

Introduction

Combine the power of LogRocket's session replay and UX analytics with your A/B testing data from Optimal UX. This integration enables product teams to identify friction points, understand user behavior, and make informed decisions about which variants truly provide the best user experience.

Why Use LogRocket for A/B Test Analysis?

  • Watch real user sessions segmented by experiment variants

  • Identify UX friction points in different variants

  • Analyze user behavior with session replay

  • Share concrete evidence across teams

  • Make informed product decisions based on actual user interactions

Step-by-Step Integration Guide

Enable the Integration

  1. Access your Optimal UX dashboard

  2. Navigate to Settings > Integrations

  3. Find the LogRocket integration card

  4. Enable the integration toggle

Understanding Data Flow

When enabled, Optimal UX automatically sends experiment participation data to LogRocket:

  • Events are tracked using LogRocket's JavaScript SDK

  • The integration uses custom events with the format:

    javascriptCopyLogRocket.track("Experiment [experiment_slug]
    
    

Security Note: Optimal UX uses experiment slugs rather than full experiment names in the tracking calls to enhance security. This prevents sensitive information about your experiments from being exposed in the tracking data.

Using Experiment Data in LogRocket

Accessing Experiment Sessions

  1. Open your LogRocket dashboard

  2. Click on "Add filters or use saved segments to refine your dashboard"

  3. Choose "Custom Event"

  4. Pick an event that starts with "Experiment "

  5. Save this as a segment

Analysis Capabilities

LogRocket’s product analytics suite provides several capabilities that help you compare and evaluate A/B test variants. Here’s a short list:

Funnel Analysis & Conversion Tracking: Build funnels that let you compare conversion rates and drop-offs between different test variants.

Custom Event Tracking: Define and retroactively apply custom events to measure key actions and KPIs for each variant.

Session Replay & Behavioral Insights: Replay sessions segmented by variant to see exactly how users interact with each version.

Frustration Metrics: Monitor signals like rage clicks, dead clicks, and error rates to gauge user frustration across variants.

User Segmentation & Filtering: Segment users into cohorts (e.g., by test group) so you can analyze performance differences in a granular way.

Cross-Functional Benefits

For Product Teams

  • Validate design decisions with real user data

  • Identify opportunities for improvement

  • Prioritize product changes based on impact

For UX Teams

  • Understand user behavior in each variant

  • Identify usability issues

  • Validate design hypotheses

For Engineering Teams

  • Monitor technical performance

  • Track error rates by variant

  • Identify browser-specific issues

For Design Teams

  • View actual user interactions

  • Validate design implementations

  • Identify design inconsistencies

Conclusion

The integration between Optimal UX and LogRocket bridges the gap between A/B testing and user experience analysis. By combining these tools, teams can make data-driven decisions based on both quantitative metrics and qualitative user behavior insights.