FullStory

Problem: A homepage test shows a statistically significant lift, but overall conversion is still below target. Stakeholders don’t understand what’s holding users back beyond the headline metrics. Solution: Convert sends experiment and variation context into FullStory, letting teams filter replays to only users in the winning variant. They can visually inspect how those visitors scroll, click, and move through the funnel. Outcome: Teams uncover specific UX friction—like overlooked CTAs or confusing form steps—behind the plateau. They ship targeted fixes and run follow‑up tests that move the winning variant closer to business goals.

Problem: A new checkout design variant loses badly in Convert reports, but analytics alone can’t explain why. Product and design teams are unsure whether to abandon or iterate on the concept. Solution: Using FullStory segments enriched with Convert’s experiment and variation names, teams watch only sessions from users who saw the losing checkout. They spot rage clicks, dead zones, and confusing copy in context. Outcome: Clear behavioral evidence shows exactly where users get stuck, enabling a redesigned variant that keeps the strategic idea but fixes execution issues. Subsequent tests recover conversions and reduce cart abandonment.

Problem: Personalized landing pages show mixed results: some segments respond well, others don’t. Aggregate metrics obscure whether the experience is genuinely helpful or just different. Solution: Convert tags each personalized experiment and variation in FullStory. Marketers build FullStory funnels and segments by variation name to compare how each audience navigates, engages with content, and reaches key events. Outcome: Teams see which personalized experiences drive confident, linear journeys and which create hesitation or pogo‑sticking. They refine targeting and messaging, leading to more effective personalization and higher segment‑level lift.

Problem: A new test variant suddenly shows a sharp drop in conversions and abnormal bounce rates. Analytics suggests something is wrong, but the issue can’t be reproduced consistently in QA. Solution: With Convert data in FullStory, teams instantly pull sessions for the affected experiment and variation. They watch real users encounter JS errors, misaligned elements, or blocked interactions in the wild. Outcome: The root cause is identified in hours instead of days. The variant is hotfixed or paused quickly, minimizing revenue loss and preventing bad experiences from skewing test results or eroding user trust.

Problem: CRO, product, and support teams work in silos. Test results live in Convert, while user complaints and behavior insights live elsewhere, making it hard to build a shared understanding of issues. Solution: Convert’s experiment and variation names appear directly in FullStory session details. Teams across functions search by experiment, review the same annotated replays, and connect tickets or feedback to specific test experiences. Outcome: Cross‑functional teams converge on a single source of behavioral truth. They prioritize fixes and new tests based on shared evidence, shortening feedback loops and improving the impact of each optimization cycle.

Problem: Organizations with strict privacy rules can’t expose experiment names in third‑party tools, limiting their ability to analyze test cohorts qualitatively without risking compliance issues. Solution: With Convert’s anonymization enabled, only experiment and variation IDs are passed into FullStory. Teams still segment and search sessions by these IDs to study behavior for each test group. Outcome: Companies maintain rigorous privacy standards while retaining full visibility into how each cohort behaves. They continue to diagnose UX issues and optimize journeys without compromising compliance or user trust.