Location intelligence UX design philosophy
TopicFrom the PointSav Documentation
The Location Intelligence interface uses a Conclusion-First design philosophy — rendering ranked tier conclusions rather than individual data points — so a user comparing markets at a national zoom level sees the most defensible commercial nodes immediately, and only drills into individual operators when a node has earned the attention.
The PointSav Location Intelligence interface uses a Conclusion-First design philosophy — rendering ranked tier conclusions rather than individual data points — so a user comparing markets at a national zoom level sees the most defensible commercial nodes immediately, and only drills into individual operators when a node has earned the attention. The interface draws inspiration from professional-grade spatial platforms where complex multi-parameter models are rendered as intuitive layered navigation surfaces rather than legend-driven dot maps. The GIS orchestration surface delivers this design at production scale.
[edit]Quality Benchmark: The Professional Map
The interface draws inspiration from professional-grade spatial platforms (e.g., meteoblue.com), where complex multi-parameter models are rendered as intuitive, layered navigation surfaces. Key design patterns adopted from this benchmark include:
- First-Class Layer Toggles: Analytical layers (Clusters, Catchment, OD Study) are presented as primary navigation controls, not secondary legend items.
- Decision-Driven Visualization: The map renders conclusions (e.g., "This node is Tier 5") rather than individual data points, allowing for rapid cross-market comparisons.
- Scale-Adaptive Legibility: Visual detail adapts dynamically to zoom level, ensuring a coherent national overview without sacrificing street-level precision.
[edit]Design Differentiation: Cluster-Grade-as-Primary-Unit
Unlike commercial GIS products that default to individual "dots on a map," the PointSav platform uses Cluster Grade as the primary visual and analytical unit. This differentiation represents a core Leapfrog 2030 design principle:
- Confidence Ramp: Sites are encoded using a single-hue color ramp (pale to deep amber). Darker, larger markers indicate higher levels of capital-validated convergence.
- Structural Guardrails: The interface enforces a strict visual hierarchy where Tier 5 and Tier 4 nodes dominate the national view, guiding the user toward the most defensible commercial nodes.
- Contextual index-cards: Clicking a cluster activates a side-drawer (not a modal) that provides immediate municipal ranking, operator chips, and institutional support counts without losing map context.
[edit]Component Architecture
The GIS surface uses a standardized component set designed for rapid re-provisioning:
- cluster-grade-marker: A five-state vector symbol with built-in accessibility labeling (D1-D5).
- location-index-card: A responsive, data-dense drawer for cluster-level metadata.
- map-layer-controls: A consistent UI panel for managing the three-layer architecture.
[edit]See also
- location-intelligence-platform — the location intelligence platform these UX patterns serve
- app-orchestration-gis — the GIS orchestration surface that implements this design
- co-location-methodology — the co-location scoring methodology that produces the tier conclusions displayed