cohort-analysis
Analyze user retention by cohort. Use when: measuring customer retention; understanding lifecycle patterns; comparing acquisition cohorts; tracking engagement over time; identifying churn risks
pinned to #a69bf67updated 2 weeks ago
Ask your AI client: “install skills/cohort-analysis”.
Requires the metahub MCP server installed in your client. Set up MCP.
mh install skills/cohort-analysismetahub onboarded this repo on the author's behalf.
If you own github.com/guia-matthieu/clawfu-skills on GitHub, claim the listing to take over publishing. Your claim preserves the existing eval history and badges; only the curator label is replaced with verified-publisher on your next publish.
Stars
132
Last commit
2 weeks ago
Latest release
published
- #ai-skills
- #anthropic
- #claude-code
- #claude-skills
- #marketing
- #mcp-server
- #prompt-engineering
- #skills
About this skill
Pulled from SKILL.md at publish time.
> Analyze retention and behavior patterns by grouping users into cohorts - understand how different customer groups behave over time.
Evaluation report
WarningsAutomated checks the publisher passed at publish time — structure, docs, safety, and whether the artifact behaves as claimed.a69bf67· 2 weeks ago
Kind-specific
31Skill: SKILL.md present
found at skills/analytics/cohort-analysis/SKILL.md · frontmatter source: SKILL.md
Skill: body content present
455 words · 3,122 chars · 16 sections · 7 code blocks
Skill: triggers declaredwarn
No `trigger` phrases in SKILL.md frontmatter
Add `trigger:` lines so Claude knows when to activate this skill — e.g. `when building MCP servers` or `for diagram creation`.
Skill: allowed-tools scope
no allowed-tools restriction (Claude may use anything)
Release history
1- releasecurrenta69bf67warn2 weeks ago
Contents
Analyze retention and behavior patterns by grouping users into cohorts - understand how different customer groups behave over time.
When to Use This Skill
- Retention tracking - Measure how users stick around over time
- Acquisition analysis - Compare cohorts from different channels
- Product changes - Measure impact on user behavior
- Churn prediction - Identify at-risk cohorts
- LTV estimation - Project customer lifetime value
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Structures analysis frameworks | Metric definitions |
| Identifies patterns in data | Business interpretation |
| Creates visualization templates | Dashboard design |
| Suggests optimization areas | Action priorities |
| Calculates statistical measures | Decision thresholds |
Dependencies
pip install pandas plotly click
Commands
Retention Analysis
python scripts/main.py retention data.csv --date-col signup --event-col purchase
python scripts/main.py retention data.csv --date-col signup --periods week
Visualize Cohorts
python scripts/main.py visualize cohorts.csv --output retention_chart.html
Export Report
python scripts/main.py report data.csv --date-col signup --event-col active --output report.html
Examples
Example 1: Analyze User Retention
python scripts/main.py retention users.csv --date-col signup_date --event-col last_active
# Output:
# Cohort Retention Analysis
# ──────────────────────────────────
# Cohort Users M1 M2 M3 M4
# Jan 2024 1,234 65% 48% 42% 38%
# Feb 2024 1,456 62% 45% 41% --
# Mar 2024 1,321 68% 52% -- --
# Apr 2024 1,567 64% -- -- --
#
# Avg Retention: 65% → 48% → 42% → 38%
# Best Cohort: Mar 2024 (68% M1)
Example 2: Generate Visual Report
python scripts/main.py report transactions.csv \
--date-col signup \
--event-col purchase_date \
--output retention_report.html
# Generates interactive HTML with:
# - Retention heatmap
# - Cohort size chart
# - Trend analysis
Cohort Table Format
| Cohort | Size | Period 0 | Period 1 | Period 2 | Period 3 |
|---|---|---|---|---|---|
| 2024-01 | 1234 | 100% | 65% | 48% | 42% |
| 2024-02 | 1456 | 100% | 62% | 45% | - |
| 2024-03 | 1321 | 100% | 68% | - | - |
Skill Boundaries
What This Skill Does Well
- Structuring data analysis
- Identifying patterns and trends
- Creating visualization frameworks
- Calculating statistical measures
What This Skill Cannot Do
- Access your actual data
- Replace statistical expertise
- Make business decisions
- Guarantee prediction accuracy
Related Skills
- ab-test-stats - Test retention experiments
- funnel-analyzer - Analyze conversion funnels
Skill Metadata
- Mode: centaur
category: analytics
subcategory: retention
dependencies: [pandas, plotly]
difficulty: intermediate
time_saved: 4+ hours/week
Reviews
No reviews yet. Be the first.
Related
Frontend Slides
Create beautiful slides on the web using Claude's frontend skills
Guizang Ppt Skill
AI-agent Skill for generating polished HTML slide decks: editorial magazine and Swiss layouts, image prompts, social covers, and a WebGL/low-power presentation runtime.
orchestration-patterns
>
mh install skills/cohort-analysis