Inspectlet

Problem: An A/B test shows a statistically significant lift, but stakeholders worry the new experience might introduce UX issues or long-term friction that numbers alone don’t reveal. Solution: Convert tags each visitor’s experiment and variation in Inspectlet, letting teams filter replays to only the winning variant and visually inspect how users navigate, scroll, and interact. Outcome: Teams validate that the winning experience is both performant and usable, increasing confidence in rollout decisions and reducing the risk of shipping a problematic variant at scale.

Problem: A variation underperforms, but funnel metrics don’t explain why users drop off or where exactly they struggle within the new experience. Solution: Using Convert’s experiment and variation tags in Inspectlet, analysts filter recordings to only the losing variation and watch real user sessions to spot confusion, rage clicks, or dead ends. Outcome: Clear qualitative evidence reveals specific UX issues to fix, enabling rapid iteration on new test variants that directly address observed friction and improve conversion rates.

Problem: For multi-step flows or complex UI changes, quantitative test results don’t fully confirm whether the original UX hypothesis about user behavior was correct. Solution: Convert passes experiment and variation names into Inspectlet as session tags, allowing teams to watch only those users exposed to a given hypothesis and see if they behave as expected. Outcome: Marketers refine or confirm their hypotheses with behavior-level evidence, designing smarter follow-up experiments that target the real drivers behind user decisions.

Problem: A new variation suddenly tanks performance, and it’s unclear whether the cause is a UX misstep, a JavaScript error, or a specific browser/device issue. Solution: With Convert’s variation data visible in Inspectlet, teams instantly filter to affected experiment sessions and watch replays to pinpoint where forms fail, elements don’t load, or buttons misfire. Outcome: Root causes are identified in hours instead of days, allowing quick hotfixes or rollbacks and minimizing revenue loss from broken or malfunctioning test experiences.

Problem: Different audience segments respond differently to the same test, but it’s hard to understand how behavior varies across segments and variations using only analytics reports. Solution: By combining Convert’s experiment/variation tags with Inspectlet’s filters, teams isolate replays for specific tests and user segments to compare how each group interacts with each variant. Outcome: Deeper insight into segment-specific behavior informs more targeted personalization experiments and helps prioritize which experiences to roll out to which audiences.

Problem: Many experiments end with no clear winner, leaving teams unsure what to change next and risking test fatigue and stalled optimization programs. Solution: Convert sends experiment and variation metadata into Inspectlet, enabling teams to review sessions for both variants and identify subtle behavior differences that metrics missed. Outcome: Even “flat” tests yield learnings about navigation patterns, content engagement, and micro-friction, fueling better-designed follow-up experiments and continuous CRO momentum.