As ACS engineers and product managers, we require usage data to make data-driven decisions about feature prioritization and understand user behavior. UX needs visibility into user flows to validate design changes.

Problem

ACS as a unit isn't as data-driven as other areas in OpenShift. Current challenges:

• Analytics results don't always show steps/page names correctly
• No clear visibility into how users move through the app
• Unable to easily identify which features are underutilized
• Session replay and heatmaps not leveraged

Goal

Enable UX and Product to make data-driven decisions by improving our analytics infrastructure and ensuring we capture meaningful, actionable data about user behavior.

Benefits

• Prioritization: Data to identify which of 3 equal-priority features to build
• User understanding: Visibility into user flows, where users get stuck
• Design validation: Metrics to measure if UX improvements work
• Feature adoption: Track which features are actually used by customers

Approach (Multi-Phase)

Phase 1: Research & Discovery

• Amplitude audit (self-serve) - understand current state
• Interview UX designers (2 people)
• Interview Product managers (2-3 people)

Phase 2: Synthesis & Discovery Doc

• Current state assessment
• UX/Product needs summary
• Gap analysis
• Prioritized recommendations

Phase 3: Technical Improvements (after research)

• Consistent page tracking
• Event naming conventions
• Standardized properties
• Developer experience improvements
• Amplitude-specific optimizations (session replay, dashboards)