pipeline-reviewlisted

# Campaign Performance Analysis ## Pipeline contract **Stage 20 of 20.** Reads the whole run folder. Writes `20-review-<YYYY-MM-DD>.md`. 1. Run `uv run scripts/check_run.py runs/<run>` — it prints the stage funnel (rows in → rows out) and flags the biggest drop. Start the review there. 2. Cut positive reply rate and meetings by `segment`, `source_type`, and `tier`. Below 30 sends in a cell, report the count and draw no conclusion. 3. Propose targeting changes (ICP filters, judge prompt, score weights, sources to add or drop) as a list for the human. Do not edit `02-client-profile.yaml`, the judge prompt, or weights yourself. 4. Approved changes start the next run at stage 2. Weekly operating cadence: `references/cold-email-weekly-rhythm.md`. Benchmarks: `references/campaign-benchmarking.md`. Files live in `runs/<run>/`. Column definitions: [`/prospecting-system`](../prospecting-system/SKILL.md). Standalone use: ignore this block. ## When to Use - Reviewing campaign results after a send cycle completes - Diagnosing why a campaign is underperforming - Comparing campaign variants to identify winners - Building performance reports for clients or leadership - Making data-driven decisions about what to scale, pause, or kill ## Framework ### The Campaign Metrics Stack Measure campaigns in layers. Each layer tells you something different about what's working and what isn't. ``` Layer 1: Deliverability → Did the email reach the inbox? Layer 2: Engagement → Did t