Retention for developers declined in Prime Video. What is your analysis plan

Problem Statement Description

Product context: Amazon is a commerce, logistics, media, devices, and cloud company; its products include Marketplace, Prime, Prime Video, Alexa devices, ads, fulfillment, and AWS. Prime Video is Amazon's streaming video service; its products include movies, series, live sports, rentals, channels, recommendations, downloads, and ad-supported viewing.

Prime Video has observed a decline in retention among developers, and you are asked to lay out an analysis plan to understand what is happening. In this context, “developers” may include internal or partner developers who use Prime Video tools, APIs, SDKs, documentation, test environments, or release workflows to build, integrate, or maintain Prime Video experiences across devices, apps, content systems, or platform services.

The focus is not to immediately propose fixes, but to structure a clear root-cause analysis. You should clarify what retention means, confirm whether the decline is real, identify where the drop is concentrated, and determine what evidence would support or reject different hypotheses. The analysis should reflect Amazon’s emphasis on operational excellence, customer obsession, and long-term platform health.

The analysis should consider:

- The exact retention metric being used, including active developer definition, time window, denominator, and expected baseline.

- Whether the decline is broad-based or concentrated by developer type, geography, device platform, API/SDK version, tenure, project type, or partner account.

- Instrumentation and data-quality checks, including tracking changes, identity stitching, bot/test accounts, logging gaps, or reporting pipeline issues.

- Recent changes that could affect developer behavior, such as tooling updates, documentation changes, API deprecations, permission changes, release process friction, or support delays.

- Workflow friction points across onboarding, development, testing, certification, deployment, debugging, and ongoing maintenance.

- External or seasonal factors, including content release cycles, partner priorities, competing platforms, organizational changes, or cloud/tooling alternatives.

- Evidence needed to prioritize hypotheses, such as funnel data, cohort trends, support tickets, developer surveys, error logs, release-cycle metrics, and qualitative interviews.

- Immediate mitigation, communication, and prevention mechanisms once the likely root cause is identified.

Your goal is to present a structured RCA plan that separates measurement issues from real behavioral decline, narrows the problem through segmentation, identifies the most likely drivers, and defines how Prime Video should monitor recovery and prevent similar retention drops in the future.