Crazy Egg

Problem: The team runs A/B tests in Convert but only sees aggregate metrics like CTR and conversion rate, making it hard to understand *why* one variation wins or loses. Solution: Convert sends experiment and variation names into Crazy Egg, which automatically creates separate heatmaps and snapshots for each variant. Marketers can visually compare clicks, taps, and scrolls across variations. Outcome: Teams quickly identify which page elements drive performance in the winning variant and what holds users back in losers. This shortens analysis cycles and informs stronger follow-up test hypotheses.

Problem: Personalized experiences built in Convert show mixed results across segments, but analysts can’t see how different audiences actually interact with the personalized content. Solution: With the Crazy Egg integration, each personalization variation gets its own snapshot. Teams visually inspect how targeted segments engage with headlines, CTAs, and modules per variant. Outcome: Marketers uncover segment-specific behavior patterns—like ignored CTAs or banner blindness—and refine personalization rules and creative, improving relevance and conversion for key audiences.

Problem: Product and UX teams know that some test variations reduce engagement, but standard analytics don’t reveal where users drop off on long pages or complex flows. Solution: Convert pushes experiment data to Crazy Egg, enabling variation-level scrollmaps and engagement heatmaps. Teams see exactly how far users scroll and where attention fades in each variant. Outcome: UX fixes are prioritized based on clear visual evidence, focusing on the sections where high-value users disengage. This leads to more impactful design changes and higher ROI from each test.

Problem: Brands operating under strict privacy rules hesitate to connect experimentation with behavioral tools for fear of exposing identifiable test data. Solution: When Convert’s Data Anonymization is enabled, experiment and variation names are replaced with IDs before being sent to Crazy Egg. Teams still get variant-level snapshots without exposing sensitive labels. Outcome: Legal and compliance teams are satisfied, while CRO teams retain the ability to visually compare behavior across variants. Experimentation scales without compromising privacy commitments.

Problem: Analysts want to slice Crazy Egg data by specific experiments and variations, but default reports don’t provide the granularity needed for advanced CRO analysis. Solution: Using the optional custom variable script, Convert passes experiment and variation names as user variables before Crazy Egg loads. These variables become filters in Crazy Egg’s Confetti view. Outcome: Teams segment clicks by experiment, variation, device, or campaign, revealing nuanced behavior patterns. This supports more sophisticated test design and better targeting decisions.