Root cause a sudden decline in retention among binge watchers using Ad-supported Plan

Problem Statement Description

Product context: Netflix is a streaming entertainment company; its products include subscription video, original films and series, recommendations, profiles, games, and ad-supported plans.

Netflix has observed a sudden decline in retention among members on the Ad-supported Plan who are classified as binge watchers. These are users who typically watch multiple episodes or long sessions in a short period, making them highly engaged but also potentially more sensitive to interruptions, content availability, playback quality, and perceived value.

Your task is to investigate the retention drop as a root-cause analysis problem. Focus on framing the anomaly clearly, validating whether it is real, identifying where the decline is concentrated, and developing hypotheses that connect user behavior, ad experience, content consumption, product changes, and external market factors.

Assume this is a medium-urgency business issue: the segment is valuable because binge watchers drive high viewing hours, but the Ad-supported Plan introduces constraints such as ad load, ad relevance, frequency capping, content licensing limitations, and plan-specific experience differences. You should reason through how to separate correlation from causation and how to determine what action Netflix should take next.

The experience should consider:

- How retention is defined for this segment, including renewal, churn, downgrade/upgrade, reactivation, and viewing inactivity.

- Whether the decline is isolated to binge watchers on the Ad-supported Plan or also visible across other plans, regions, devices, content genres, or tenure cohorts.

- Instrumentation checks for retention tracking, ad delivery logs, playback events, subscription status, content availability, and user classification as a binge watcher.

- Segmentation by geography, device type, ad load, ad frequency, session length, title type, new versus existing subscribers, and recent plan joiners.

- Hypotheses across product experience, ad experience, streaming quality, recommendation changes, content catalog gaps, pricing/value perception, and competitor activity.

- Evidence needed to prioritize causes, such as changes in completion rate, session abandonment, ad-related exits, customer support contacts, cancellation reasons, and survey feedback.

- Short-term mitigation options versus longer-term prevention mechanisms, without assuming a single root cause upfront.

The goal is to demonstrate a structured RCA approach that helps Netflix determine whether the retention decline is due to measurement error, user mix, ad experience degradation, content or discovery issues, technical quality, competitive pressure, or a combination of factors, and to define what evidence would guide the next product or operational response.