A fragmented experience
When I joined Atlassian's Admin Experience team, the 20+ Admin Analytics charts dispalying org-level data on apps, users, and security had diverged from the company's new visualization pattern (VP) design system. Titles, labels, and date-range content patterns varied widely, making it harder for admins to scan and act. These inconsistencies led me to my main objective: how might we bring Analytics chart into VP alignment while documenting the standards so future updates stay consistent?
Scoping the problem → writing and validating content solutions
I audited all 20+ charts and narrowed the work to five high-impact areas tied to core admin JTBDs (e.g., external user monitoring, security policy validation). Focusing on the highest-value charts kept the scope achievable and impact measurable. I drafted new titles, axis labels, and empty states, then ran critique reviews with design, PM, and content partners to maximize VP alignment and content clarity. In parallel, I refreshed Analytics support documentation so product UI and help content represented a unified Analytics experience for admins.
Scaling content consistency with AI
- To make design critiques more efficient and productive, I built an Admin content pattern checker agent: a lightweight Rovo (Atlassian AI) agent that scanned UI copy for Admin-specific content patterns (e.g., date-range phrasing, sentence casing, terminology). The agent flagged discrepancies in seconds, helping me catch issues early and giving reviewers a shared reference during copy critiques.
What shipped?
- Clear, VP-aligned copy across priority charts, improving scanability and comprehension.
- AI Content-Pattern Checker integrated into the team's workflow, accelerating reviews and serving as a living style-guide reference.
- First-ever official docs for Jira analytics charts and standardized "Date range" x-axis language.
- Reduced duplication by merging overlapping external-user security charts.