Design an experimentation dashboard for Stock

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 Stock serves small businesses that need fast access to high-quality images, videos, templates, and AI-assisted creative assets for marketing, websites, social, and document workflows. Product teams may run experiments across discovery, search, licensing, pricing, onboarding, contributor content, and integrations with Adobe creative tools, and they need a clear way to understand whether experiments improve customer outcomes without harming trust, quality, or monetization.

Design an experimentation dashboard for Adobe Stock focused on small-business users. The dashboard should help product managers, designers, data scientists, and business stakeholders monitor active and completed A/B tests, interpret results, compare impact across cohorts, and make confident launch, iterate, or stop decisions.

Your scope is not to solve a single experiment, but to define what the dashboard should measure and how it should make experimentation results useful. Consider the full user journey from landing on Stock, searching or browsing assets, previewing, licensing, downloading, using assets in Adobe workflows, and potentially returning for future projects.

The experience should consider:

- Primary success metrics, including how each metric is defined, its denominator, and why it matters for Adobe Stock and small businesses.

- Funnel metrics across discovery, search, asset evaluation, licensing, download, and repeat usage.

- Experiment metadata such as hypothesis, audience, variants, exposure rules, start/end dates, sample size, confidence, and decision status.

- Cohorts and segmentation, such as new versus returning users, subscribers versus pay-as-you-go customers, business size, geography, asset type, traffic source, and Adobe app integration users.

- Instrumentation requirements, including event logging, exposure tracking, attribution windows, deduplication, and data freshness.

- Guardrail metrics for revenue, conversion quality, cancellation, search relevance, asset quality, latency, licensing errors, customer support contacts, and brand trust.

- Decision usefulness, including how the dashboard should highlight statistically meaningful outcomes, ambiguous results, underpowered tests, and conflicting trade-offs.

- Collaboration needs for PMs, analysts, designers, engineers, and executives reviewing experiment outcomes.

The goal is to describe a metrics dashboard that enables Adobe Stock teams to run disciplined experimentation, understand customer and business impact, and make reliable product decisions for the small-business segment while preserving creative workflow quality and professional trust.