Root cause a sudden decline in retention among students using Photoshop at global scale

Problem Statement Description

Product context: Adobe is a creative, document, and marketing software company; its products include Creative Cloud, Photoshop, Illustrator, Acrobat, Adobe Express, Firefly, and Experience Cloud.

Adobe Photoshop has seen a sudden decline in retention among student users at global scale. You are asked to investigate the issue as a product manager responsible for understanding whether the drop reflects a real behavioral change, a measurement problem, a localized incident, or a broader shift in student needs and alternatives.

The affected users are students who use Photoshop for coursework, personal creative projects, portfolios, internships, clubs, and early professional work. Their workflows may span desktop and mobile, school-managed licenses and individual subscriptions, cloud documents, generative AI features, tutorials, templates, plugins, and collaboration with classmates or instructors.

This is a root-cause analysis problem. The focus is not to propose a growth plan immediately, but to structure how you would diagnose the retention decline, isolate the drivers, validate evidence, assess severity, and determine what Adobe should do next to protect the student experience and business.

The experience should consider:

- How to define the retention metric precisely, including time window, denominator, student eligibility, subscription status, device/platform, and what counts as active Photoshop usage.

- How to validate whether the decline is real by checking instrumentation changes, event logging, identity resolution, academic-license tagging, data latency, seasonality, and reporting pipeline issues.

- How to segment the anomaly by geography, school type, plan type, acquisition channel, operating system, app version, feature usage, new versus existing students, and cohort start date.

- How to form hypotheses across product experience, pricing or licensing, onboarding, performance, feature changes, AI-related workflows, cloud storage, collaboration needs, and competitive substitution.

- How to inspect funnel and behavioral evidence, such as activation, first project creation, tutorial completion, export/share actions, crash rates, login failures, billing interruptions, and support contacts.

- How to distinguish expected academic calendar effects from abnormal retention changes across regions with different term schedules and student purchasing cycles.

- How to evaluate external factors, including campus software bundles, competitor adoption, shifts toward simpler design tools, generative AI tools, or course curriculum changes.

- How to prioritize mitigation, communication, and prevention once evidence points toward a likely root cause or set of contributing causes.

Your goal is to demonstrate a rigorous RCA approach suitable for a high-scale creative software product: frame the anomaly clearly, verify the data, narrow the problem through segmentation, connect hypotheses to evidence, recommend next investigative or mitigation steps, and define how Adobe would monitor recovery without jumping prematurely to a solution.