Build a metric tree for Photoshop after a major redesign 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 has recently rolled out a major redesign of Photoshop globally, with particular concern for how students adopt, learn, and continue using the product. The redesign may affect core creative workflows such as opening or creating files, editing images, using generative AI features, saving/exporting work, collaborating, and moving work across Adobe’s broader creative ecosystem.

You are being asked to build a metric tree that helps Adobe understand whether the redesign is successful at global scale. The metric tree should connect high-level business and user outcomes to measurable product behaviors, while accounting for the fact that Photoshop serves both deep professional workflows and newer student users who may compare the experience with tools like Canva, Figma, CapCut, or AI-native creation products.

This is a metrics interview question, so the focus is not on proposing product features. The emphasis is on defining the right success metric structure, explaining denominators and cohorts clearly, identifying leading and lagging indicators, and ensuring the metrics are instrumented in a way that can support decisions after a large redesign.

The experience should consider:

- The primary outcome Photoshop should optimize for after the redesign, especially for students globally.

- How to separate acquisition, activation, engagement, retention, monetization, and creative output quality within the metric tree.

- Clear metric definitions, including denominators such as new users, active students, trial users, subscribers, returning users, or collaborative users.

- Key workflow steps to instrument, from onboarding and first project creation to editing depth, AI feature usage, export/share, and repeat usage.

- Cohorts and segments, including geography, device/platform, student plan type, experience level, new versus existing users, and pre-redesign versus post-redesign users.

- Guardrail metrics for workflow disruption, performance, crashes, latency, feature discoverability, support contacts, cancellation, and trust in AI-generated outputs.

- How metrics should help Adobe distinguish short-term novelty effects from durable product value and learning-curve improvements.

- How the metric tree can support decision-making on whether to iterate, roll back parts of the redesign, invest in education/onboarding, or expand specific workflows.

Your goal is to frame a rigorous, decision-useful metric tree for Photoshop’s redesign that reflects Adobe’s global scale, student user needs, creative workflow depth, and the risks of changing a mature professional product.