Golden Data · the thesis

One engine, many roles

Everything in this portfolio runs on the same analytical engine — a full-funnel model, LTV, experimentation, executive scorecards, and Voice-of-Customer. I build it once and point it wherever the question is: at a lease-to-own book, at a competitor, at a specific job description. The companies change; the rigor doesn’t. That’s the whole idea — and the reason a hiring manager can see exactly what I’d do for them before the first conversation.

Jun 22, 2026

The engine

Five parts. Together they take a customer question from data to a decision an executive will act on.

The lanes

The same engine, instantiated five ways. Each lane is the others seen from a different angle.

Deep data products

Interactive, calibrated builds — a customer-performance model and a market-intelligence briefing for Upbound.

Competitor spotlights

Deep dives on the field, every figure sourced — they interlock into one competitive map.

JD case studies

The engine pointed at a specific role — mandate, 90-day plan, signature analysis, proof.

AI-enabled operator

The portfolio as proof — a dozen-plus cited analyses shipped through an AI research→build model I designed.

Salary intelligence

The roles turned into a data asset — posted comp across role families, alongside the IC-role salary dashboard.

Built by Paul Brown

If a role needs customer-lifecycle analytics, competitive intelligence, decisioning, or an AI-enabled operator who ships responsibly — it’s the same person and the same engine. Pick the lane that matches your opening, or browse them all.