---
name: segment-analysis
description: "Analyze user segments, cohorts, and customer groups using PostHog data. Creates retention tables, compares segment behavior, and generates group breakdowns. Use when the user asks about customer segmentation, cohort retention, user group comparison, churn analysis, or funnel analysis by segment."
disable-model-invocation: false
allowed-tools: Task, TodoWrite
version: 1.0.0
---

# Segment Analysis

Deep-dive into specific user segments, cohorts, or customer groups using PostHog data.

## Usage

```bash
/segment-analysis <segment-description>

Examples:
  /segment-analysis "users from paid plans vs free plans"
  /segment-analysis "power users who use feature X daily"
  /segment-analysis "users who churned in last 30 days"
  /segment-analysis "cohort: signed up in Q4 2024"
```

## What This Analyzes

### User Segments

- By plan type (free, pro, enterprise)
- By geography (country, region)
- By acquisition source (organic, paid, referral)
- By behavior (power users, casual users, at-risk)

### Cohort Analysis

- By signup date (monthly, weekly cohorts)
- By first feature used
- By activation milestone reached
- By engagement level

### Comparison Analysis

- Segment A vs Segment B
- Before/after feature launch
- Treatment vs control (A/B tests)
- Time period comparisons

## Example Analyses

### Plan Comparison

```bash
/segment-analysis "Compare engagement patterns between free and paid users: session frequency, feature usage, retention"
```

### Power User Identification

```bash
/segment-analysis "Identify our power users: who are they, what features do they use, what's their profile?"
```

### Churn Analysis

```bash
/segment-analysis "Analyze users who churned: what were their last actions, which features didn't they use?"
```

### Geographic Performance

```bash
/segment-analysis "Compare conversion rates and engagement across our top 5 countries"
```

### Cohort Retention

```bash
/segment-analysis "Show retention curves for each monthly signup cohort in 2024"
```

## Output Format

Analysis typically includes:

- **Segment characteristics** (size, demographics, behavior)
- **Key metrics** for each segment
- **Comparative insights** between segments
- **Behavior patterns** unique to segment
- **Recommendations** for targeting or improvement

## Segmentation Criteria

You can segment by:

- **Demographics**: Country, language, device type
- **Behavior**: Feature usage, session frequency, engagement score
- **Business**: Plan type, payment history, LTV
- **Temporal**: Signup date, last active, tenure
- **Custom**: Any event or property in PostHog

## Advanced Analysis

### Multi-dimensional Segmentation

```bash
/segment-analysis "Power users (5+ sessions/week) from enterprise plans who use feature X"
```

### Funnel by Segment

```bash
/segment-analysis "Compare signup to activation funnel for organic vs paid traffic"
```

### Retention by Segment

```bash
/segment-analysis "30-day retention by initial feature used"
```

## Tips for Better Analysis

1. **Be specific** - Define your segment clearly
2. **Ask for comparisons** - "vs" between segments reveals insights
3. **Look for patterns** - What makes segments different?
4. **Consider time** - Trends over time matter
5. **Combine criteria** - Multi-dimensional segments can be revealing

## Context Cost

Plugin uses ~40k tokens. Disable when analysis is complete:

```bash
/plugin disable catalyst-analytics
```

---

**See also**: `/catalyst-analytics:analyze-user-behavior`, `/catalyst-analytics:product-metrics`