Customer Intelligence Graph is a recruiter-ready flagship frontend that maps how accounts, lifecycle campaigns, product usage, partner influence, trust risk, and experimentation outcomes compound into real commercial decisions.

Instead of showing one more KPI board, it translates customer intelligence into a relationship surface: nodes, edges, pressure paths, narrative threads, and action-ready insights.

This project shows how I think when a company needs more than a dashboard:

• I turn fragmented growth, revenue, and lifecycle signals into a coherent operating model.
• I design internal products that help leadership understand why a commercial outcome is happening, not just what changed.
• I build interfaces that connect technology, operations, GTM, and narrative decision-making.

Most growth and revenue teams can see events. Fewer can see relationships.

Customer Intelligence Graph is framed around a simple idea: the most important commercial decisions usually live between systems, not inside any single one. Revenue, lifecycle motion, experimentation, product usage, support drag, and trust signals all shape the customer story, but they are often reviewed in separate dashboards owned by different teams.

This interface compresses those fragments into one connected surface.

flowchart LR
    A["Strategic Account"] --> B["Usage Pulse"]
    B --> C["Lifecycle Campaign"]
    C --> D["Partner Influence"]
    B --> E["Trust Risk"]
    D --> E
    E --> F["Experiment Intervention"]
    F --> A

Additional implementation notes live in docs/architecture.md.

Set-Location "C:\Users\chaus\dev\repos\customer-intelligence-graph"
npm install
npm run dev

npm test
npm run build
npm run lint

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