# Funnel analysis skill Human Guide

## What This Is For
Analyze user conversion funnels, calculate step-by-step conversion rates, create interactive visualizations, and identify optimization opportunities. It gives the agent a clearer input/output frame for funnel analysis skill: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the Funnel analysis skill agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for funnel analysis skill.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the Funnel analysis skill guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- **Build conversion funnels** from multi-step user data
- **Calculate conversion rates** between each step
- **Perform segmentation analysis** by different user attributes
- **Create interactive visualizations** with Plotly
- **Generate business insights** and optimization recommendations
- Marketing campaign analysis (promotion → purchase)
- User onboarding flow analysis
- Website conversion funnel optimization
- Lead nurturing process analysis
- User journey steps (clicks, page views, actions)
- User identifiers (customer_id, user_id, etc.)
- Timestamps or step indicators

## Decision Points And Nuance
The original skill emphasizes: Quick Start, When to Use, Key Requirements, Core Workflow, Data Preparation, Analysis Process, Output Deliverables, Example Usage Scenarios, E-commerce Purchase Funnel, User Registration Funnel.

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- Install required packages:

## Copy-And-Paste Prompt
```text
Use the Funnel analysis skill human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the liangdabiao/claude-data-analysis-ultra-main skill entry for `funnel-analysis`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# Funnel Analysis Skill

Analyze user behavior through multi-step conversion funnels to identify bottlenecks and optimization opportunities in marketing campaigns, user journeys, and business processes.

## Quick Start

This skill helps you:
1. **Build conversion funnels** from multi-step user data
2. **Calculate conversion rates** between each step
3. **Perform segmentation analysis** by different user attributes
4. **Create interactive visualizations** with Plotly
5. **Generate business insights** and optimization recommendations

## When to Use

- Marketing campaign analysis (promotion → purchase)
- User onboarding flow analysis
- Website conversion funnel optimization
- App user journey analysis
- Sales pipeline analysis
- Lead nurturing process analysis

## Key Requirements

Install required packages:
```bash
pip install pandas plotly matplotlib numpy seaborn
```

## Core Workflow

### 1. Data Preparation
Your data should include:
- User journey steps (clicks, page views, actions)
- User identifiers (customer_id, user_id, etc.)
- Timestamps or step indicators
- Optional: user attributes for segmentation (gender, device, location)

### 2. Analysis Process
1. Load and merge user journey data
2. Define funnel steps and calculate metrics
3. Perform segmentations (by device, gender, etc.)
4. Create visualizations
5. Generate insights and recommendations

### 3. Output Deliverables
- Funnel visualization charts
- Conversion rate tables
- Segmented analysis reports
- Optimization recommendations

## Example Usage Scenarios

### E-commerce Purchase Funnel
```python
# Steps: Promotion → Search → Product View → Add to Cart → Purchase
# Analyze by device type and customer segment
```

### User Registration Funnel
```python
# Steps: Landing Page → Sign Up → Email Verification → Profile Complete
# Identify where users drop off most
```

### Content Consumption Funnel
```python
# Steps: Article View → Comment → Share → Subscribe
# Measure engagement conversion rates
```

## Common Analysis Patterns

1. **Bottleneck Identification**: Find steps with highest drop-off rates
2. **Segment Comparison**: Compare conversion across user groups
3. **Temporal Analysis**: Track conversion over time
4. **A/B Testing**: Compare different funnel variations
5. **Optimization Impact**: Measure changes before/after improvements

## Integration Examples