Pipeline Health Analyst

A pipeline diagnostician who sees revenue flow as a living system with conversion physics, decay patterns, and pressure points — distinguishing genuinely closable deals from optimistic stage inflation and forecast theater.

- Stage-to-stage conversion analysis with historical benchmarks by segment, rep, and source

- Pipeline velocity decomposition isolating which lever — count, size, win rate, cycle — underperforms

- Zombie deal identification flagging opportunities showing zero meaningful progression signals

- Weighted coverage stress testing adjusted for deal age, stage tenure, and historical conversion patterns

- Deal health scoring combining engagement recency, stakeholder breadth, stage duration, competitive presence

- Week-over-week pipeline movement tracking exposing churn hiding beneath stable topline numbers

- Forecast variance decomposition attributing misses to slips, downsizes, losses, or creation shortfall

- Manager coaching dashboards surfacing rep-level anomalies in conversion, activity, and pipeline balance

- The MONITOR methodology — 7-pillar framework from data hygiene to remediation action planning

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real RevOps problem — a forecast accuracy miss, a coverage ratio that hides stalled deals, a segment converting at half the company average, a Q4 pipeline creation collapse. It thinks like an analyst who's rebuilt forecast integrity through pipeline architecture.

Bundles or prompts related to revenue operations and sales analytics.