• Design Rationale:
  ‍Users tend to mentally organize performance data by relevance. Splitting strategies into "Active" and "Inactive" groups reduces visual clutter, making it easier to focus on current performance.
  ‍Benchmarks: I took cues from Google Analytics and Asana, which segment tasks by status to align with user intent. Zapier also applies similar logic when organizing workflows by active/historical state.
• Hypothesis:
  ‍A segmented view will shorten the time users need to locate current strategies, leading to faster interactions and more confident decision-making.
• Trade-off:
  ‍Grouping data requires clear status logic and adds vertical space. Users with large datasets may need to scroll more, so layout and pagination must be well-balanced.
• Validation:
  We can use Tree Testing or Card Sorting to verify grouping logic, track click-through rates in the "Active" section, and gather feedback via clarity-focused satisfaction surveys.

3. Advanced Filter Panel with Hierarchy, Range & Multi-Condition Support

• Rationale
  The original filter system only supported basic, flat filtering. It lacked the ability to segment users based on relational hierarchy (Parent / Layer), asset range, or user name. To improve performance discovery and competitive comparison, I introduced a redesigned Advanced Filter Panel featuring:

• structured filter sections (Layer, Parent, Name)
• a visual asset range slider with histogram
• quick toggles for Top 3 / 5 / 10 performers

Benchmarks:
I drew inspiration from Dune Analytics and Amazon Seller Central for multi-condition filter layout, and from LinkedIn Recruiter and Figma Team Browser for hierarchical search patterns and visual range sliders paired with data context.

• Hypothesis:
  ‍A structured, multi-condition filter experience will enable users to identify and compare relevant performers faster (e.g., "Top 5 users within $1,000–$5,000 range"), leading to better engagement and retention.
• Trade-off:
  ‍Adding more filter layers increases UI complexity and may introduce a learning curve for first-time users. To address this, I prioritized clear sectioning, defaults, and progressive disclosure to reduce overwhelm.
• Validation:
  ‍In future iterations, we can validate this solution through:

• First-click testing to assess discoverability and correct usage of the filter panel
• Feature usage tracking to measure how often users engage with filters like Layer, range, or Top N shortcuts, and whether these lead to higher interaction rates
• Task-based usability tests simulating user goals (e.g., “Find the top 3 subordinates in a specific strategy”) to measure accuracy and efficiency

Prototype