Retention fell after a redesign of video meeting experience. Investigate the issue

Problem Statement Description

A recently redesigned video meeting experience has launched to users, and retention has fallen afterward. The product is used heavily by operations managers who rely on recurring meetings, cross-functional coordination, shift handoffs, incident reviews, and performance check-ins to keep teams aligned. The decline may reflect a true loss of product value, disruption in established workflows, measurement artifacts, rollout issues, or segment-specific friction introduced by the redesign.

Your task is to investigate the retention drop as a root-cause analysis problem. Focus on how you would frame the anomaly, validate whether it is real, identify affected user cohorts, form hypotheses, and determine what evidence would confirm or reject each hypothesis. The investigation should connect product behavior to meeting effectiveness, not just surface-level engagement.

Assume the redesign may have changed parts of the meeting workflow such as joining meetings, scheduling, in-call controls, screen sharing, chat, recordings, participant management, notifications, or post-meeting follow-up. Operations managers may be especially sensitive to reliability, speed, predictability, accessibility, and the ability to run structured meetings across distributed teams.

The experience should consider:

- How retention is defined, including user-level versus account-level retention, time window, denominator, and whether recurring meeting behavior is captured correctly.

- Whether the retention drop is statistically meaningful and aligned with the redesign rollout timeline, geography, platform, account type, and adoption exposure.

- Segmentation by operations managers versus other personas, meeting frequency, meeting size, device, network quality, company size, and new versus existing users.

- Instrumentation checks for event logging changes, tracking gaps, identity stitching, bot/guest handling, meeting attendance attribution, or changes in retention calculation.

- Funnel and workflow analysis across key meeting actions such as schedule, join, host, share, collaborate, record, end meeting, and follow up.

- Hypotheses around usability friction, performance regressions, feature discoverability, accessibility issues, trust concerns, admin-policy conflicts, or disrupted team routines.

- Evidence sources such as product analytics, session replays where appropriate, support tickets, customer interviews, incident logs, latency/error metrics, and cohort comparisons.

- Mitigation and prevention planning, including short-term containment, rollback or feature-flag options, user communication, monitoring, and safeguards for future redesign launches.

The goal is to demonstrate a structured RCA approach that separates correlation from causation, identifies the highest-impact affected users and workflows, and leads to a clear path for restoring retention and meeting effectiveness without prematurely jumping to a solution.