LogRocket

Problem: A variation wins on conversion rate, but UX and support teams keep hearing that something feels confusing. Aggregate analytics don’t reveal what’s actually going wrong in the user journey. Solution: Convert flags each user’s experiment and variation in LogRocket as a “Convert Experience” event. Teams filter LogRocket sessions by the winning variation and replay real journeys to see friction, confusion, or workarounds. Outcome: Product and UX teams refine the winning variation instead of shipping hidden UX debt. This preserves the uplift while reducing complaints, lowering support tickets, and improving long-term satisfaction.

Problem: An A/B test variation suddenly underperforms, but analytics only show a drop in conversions. It’s unclear whether the issue is UX, performance, or a technical bug affecting only that variant. Solution: Using the Convert Experience event, teams filter LogRocket sessions to only the underperforming variation. Session replays reveal JS errors, broken buttons, or layout issues that occur exclusively in that variant. Outcome: Teams quickly fix variation-specific bugs instead of killing promising ideas. This shortens debugging cycles, salvages experiments, and prevents revenue loss from silent, variant-only defects.

Problem: Two variations show similar conversion rates, but stakeholders suspect one drives better engagement and long-term value. Standard reports don’t capture qualitative differences in how users interact. Solution: Convert passes experiment and variation IDs into LogRocket, enabling side-by-side dashboards and filtered replays by variation. Teams compare clicks, scroll depth, rage clicks, and form interactions across variants. Outcome: Marketers choose the variation that not only converts but also delivers healthier engagement patterns. This leads to better downstream retention, fewer frustrations, and more defensible experiment decisions.

Problem: After launching an experiment, error rates and complaints spike, but only for some users. It’s hard to know whether the experiment is to blame or if an unrelated issue is at play. Solution: Convert’s experiment data appears in every LogRocket session, so teams filter sessions by experiment and variation to see if errors cluster around a specific test. Replays show exactly when and how failures occur. Outcome: Teams rapidly confirm or rule out experiments as the source of incidents. They can roll back or hotfix affected variations with confidence, reducing downtime, churn risk, and internal firefighting.

Problem: A form-focused A/B test shows one variation with a slightly higher completion rate, but abandonment patterns and field-level friction remain unclear. Analytics alone can’t show where users struggle. Solution: Convert tags each session with the active form experiment and variation in LogRocket. Teams filter replays by variation to watch users fill fields, encounter validation errors, or hesitate on specific steps. Outcome: Insights from real sessions drive targeted form changes—copy tweaks, error messaging, field order, or step reduction. This lifts completion rates beyond the original test win and improves lead quality.

Problem: Experiment results live in Convert, while behavior metrics and UX issues live in LogRocket, making it hard to see a unified picture of how tests affect user experience over time. Solution: With Convert Experience events flowing into LogRocket, teams create dashboards segmented by experiment and variation. They track clicks, errors, performance, and frustration signals per variant. Outcome: Stakeholders monitor both conversion and UX health for every test in one place. This supports continuous optimization, prevents shipping UX-negative winners, and aligns product, UX, and growth teams.