State-level analytics for election campaign teams.
Project brief
Made dense election data easier to scan with KPI tiles, drill-down maps, hover states, and constituency context.
Hiring signal
Senior ownership across product framing, scope, and shipped interface quality.
Engineering detail
Focus on constraints, architecture choices, external systems, and data flow.
A state-level analytics dashboard built for campaign teams working with dense regional data under compliance constraints, surfacing the numbers that matter without burying the reader in them.
Campaign and civic data is naturally hierarchical — state, region, constituency — and most dashboards either flatten it into one overwhelming view or force a slow drill-down for every question.
I focused the frontend architecture on progressive disclosure: a state-level overview that stays legible at a glance, with drill-down views that load only the data the viewer has actually asked for, kept fast and standards-compliant throughout.
Project method
The dashboard needed to make dense election data scannable for campaign teams: national view, state drill-down, constituency detail, turnout, vote share, alliance splits, and trend context across election years. The key requirement was speed of interpretation, not just chart coverage.
Vite and React kept the dashboard fast and client-focused, TypeScript protected the regional data model, Zustand handled navigation and selection state, TanStack Query was available for data workflows, and D3 powered the custom map and charting needs that generic dashboard components would not cover well.
The interface moved toward an atomic structure with atoms such as StatNumber, ProgressBar, Sparkline, Badge, and ChartTooltip; molecules such as MetricCard and PartyBreakdown; and organisms such as StateMap and historical charts. Design tokens such as bg-base, bg-header, bg-surface, border, text-primary, text-muted, nda, india, others, and info kept the analytics UI consistent.
The MVP was an India-to-state drill-down with year switching for 2014, 2019, and 2024, KPI cards, alliance comparison, map interaction, and constituency-level panels. Authentication, advanced filtering, and broader campaign tooling were secondary to proving the core exploration flow.
The project progressed from normalized election data and hash-based navigation into bento-style dashboard composition. Once the state selection model worked, maps, trend sparklines, vote-share donuts, and constituency panels were layered in to support progressively deeper analysis without forcing full page transitions.
Takeaway
A dashboard that scales from a statewide summary down to constituency-level detail without a full page reload, with accessibility and data accuracy treated as first-class requirements.
Evidence
Open channel
Architecture, AI workflows, design systems, and interfaces that need to hold up after launch.