32 lines
1.2 KiB
Markdown
32 lines
1.2 KiB
Markdown
---
|
||
name: cohort-analysis
|
||
description: Standard method for slicing bookings, pipeline, and retention cohorts
|
||
for diagnostics.
|
||
---
|
||
|
||
# Cohort Analysis Framework Skill
|
||
|
||
## When to Use
|
||
- Comparing performance across acquisition channels, segments, or product lines.
|
||
- Diagnosing conversion drop-offs within specific booking/vintage cohorts.
|
||
- Stress-testing forecast assumptions with historical baseline behavior.
|
||
|
||
## Framework
|
||
1. **Cohort Definition** – choose cohort key (signup month, lead source, product tier, segment).
|
||
2. **Metric Stack** – select KPIs (coverage, win rate, ACV, NRR, payback) per cohort.
|
||
3. **Normalization** – adjust for seasonality, deal size mix, or currency.
|
||
4. **Visualization** – waterfall tables, heatmaps, or overlapping curves to highlight divergence.
|
||
5. **Narrative Layer** – annotate drivers, anomalies, and recommended actions.
|
||
|
||
## Templates
|
||
- Cohort definition worksheet (keys, filters, inclusion/exclusion rules).
|
||
- Standardized chart pack for leadership readouts.
|
||
- Diagnostic checklist for follow-up analyses.
|
||
|
||
## Tips
|
||
- Keep cohorts mutually exclusive to avoid double-counting.
|
||
- Pair with `inspect-pipeline-levers` to link cohort insights to pipeline stages.
|
||
- Rebaseline quarterly so assumptions stay current.
|
||
|
||
---
|