How do I install the Retention Deep Dive skill?

Run npx skillmds@latest add nandanosql/retention-deep-dive in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Retention Deep Dive safe to use?

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Which AI agents work with Retention Deep Dive?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Retention Deep Dive free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Retention Deep Dive?

nandanosql (@nandanosql) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Retention Deep Dive by nandanosql — Agent Skill

Name: Retention Deep Dive
Author: nandanosql

File contents

Purpose

Analyze why users stay or leave through cohort analysis, retention curve benchmarking, churn pattern identification, and re-engagement strategy design.

Application

Step 1: Build Retention Cohorts

## Retention Cohort Table

| Cohort | D1 | D7 | D14 | D30 | D60 | D90 |
|--------|----|----|-----|-----|-----|-----|
| Jan 2026 | [%] | [%] | [%] | [%] | [%] | [%] |
| Feb 2026 | [%] | [%] | [%] | [%] | [%] | [%] |
| Mar 2026 | [%] | [%] | [%] | [%] | [%] | [%] |

Step 2: Analyze the Curve Shape

**Curve type:** [📉 Declining → Flat | 📉 Continuous decline | 📈 Smile curve]
**Flattening point:** [Day/Week when retention stabilizes]
**Benchmark:** [Industry average for our product type]
**Health verdict:** [Healthy / Needs work / Critical]

Step 3: Churn Analysis

## Top Churn Reasons (from data + user research)

| Reason | % of Churners | Segment | Intervention |
|--------|-------------|---------|-------------|
| [Reason 1] | [%] | [Who] | [What to do] |
| [Reason 2] | [%] | [Who] | [What to do] |
| [Reason 3] | [%] | [Who] | [What to do] |

Step 4: Retention Strategies

## Retention Improvement Plan

### Short-term (This Quarter)
- [Action 1 — targeting biggest churn reason]
- [Action 2 — quick win]

### Medium-term (Next Quarter)
- [Habit loop design — trigger, action, reward]
- [Engagement feature]

### Long-term (6+ months)
- [Product moat — data, network, switching cost]

Quality Rubric

Dimension	0	1	2
Cohort Data	No cohorts	Monthly cohorts	Weekly/monthly + segmented
Churn Reasons	Assumed	Survey data	Multi-source (data + interviews + analytics)
Benchmarking	No comparison	Industry average	Industry + historical trend
Strategies	"Improve the product"	Specific ideas	Prioritized by impact + effort

References

Related Skills

skills/analytics/funnel-analysis/SKILL.md — Pipeline to retention
skills/growth/activation-optimization/SKILL.md — Activation drives D1 retention
skills/analytics/cohort-analysis/SKILL.md — Cohort method deep dive
skills/growth/ab-test-design/SKILL.md — Test retention interventions

Skill type: Component Domain: Growth & Optimization

---name: retention-deep-divedescription: Analyze user retention by building cohort charts, identifying retention drivers, diagnosing churn patterns, and designing re-engagement strategies.---## PurposeAnalyze **why users stay or leave** through cohort analysis, retention curve benchmarking, churn pattern identification, and re-engagement strategy design.---## Application### Step 1: Build Retention Cohorts```markdown## Retention Cohort Table| Cohort | D1 | D7 | D14 | D30 | D60 | D90 ||--------|----|----|-----|-----|-----|-----|| Jan 2026 | [%] | [%] | [%] | [%] | [%] | [%] || Feb 2026 | [%] | [%] | [%] | [%] | [%] | [%] || Mar 2026 | [%] | [%] | [%] | [%] | [%] | [%] |```### Step 2: Analyze the Curve Shape```markdown**Curve type:** [📉 Declining → Flat | 📉 Continuous decline | 📈 Smile curve]**Flattening point:** [Day/Week when retention stabilizes]**Benchmark:** [Industry average for our product type]**Health verdict:** [Healthy / Needs work / Critical]```### Step 3: Churn Analysis```markdown## Top Churn Reasons (from data + user research)| Reason | % of Churners | Segment | Intervention ||--------|-------------|---------|-------------|| [Reason 1] | [%] | [Who] | [What to do] || [Reason 2] | [%] | [Who] | [What to do] || [Reason 3] | [%] | [Who] | [What to do] |```### Step 4: Retention Strategies```markdown## Retention Improvement Plan### Short-term (This Quarter)- [Action 1 — targeting biggest churn reason]- [Action 2 — quick win]### Medium-term (Next Quarter)- [Habit loop design — trigger, action, reward]- [Engagement feature]### Long-term (6+ months)- [Product moat — data, network, switching cost]```---## Quality Rubric| Dimension | 0 | 1 | 2 ||-----------|---|---|---|| **Cohort Data** | No cohorts | Monthly cohorts | Weekly/monthly + segmented || **Churn Reasons** | Assumed | Survey data | Multi-source (data + interviews + analytics) || **Benchmarking** | No comparison | Industry average | Industry + historical trend || **Strategies** | "Improve the product" | Specific ideas | Prioritized by impact + effort |---## References### Related Skills- `skills/analytics/funnel-analysis/SKILL.md` — Pipeline to retention- `skills/growth/activation-optimization/SKILL.md` — Activation drives D1 retention- `skills/analytics/cohort-analysis/SKILL.md` — Cohort method deep dive- `skills/growth/ab-test-design/SKILL.md` — Test retention interventions---**Skill type:** Component**Domain:** Growth & Optimization

Frequently asked questions

Retention Deep Dive