Funnel Analysis Agent Skill
Analyze user conversion funnels, calculate step-by-step conversion rates, create interactive visualizations, and identify optimization opportunities. Use when working with multi-step user journey data, conversion analysis, or when user mentions funnels, conversion rates, or user flow analysis.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/nicepkg/ai-workflow --skill funnel-analysisThe instruction itself
15 sections, as written by the authorFunnel 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:
- 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
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:
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
- Load and merge user journey data
- Define funnel steps and calculate metrics
- Perform segmentations (by device, gender, etc.)
- Create visualizations
- 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
# Steps: Promotion → Search → Product View → Add to Cart → Purchase
# Analyze by device type and customer segment
User Registration Funnel
# Steps: Landing Page → Sign Up → Email Verification → Profile Complete
# Identify where users drop off most
Content Consumption Funnel
# Steps: Article View → Comment → Share → Subscribe
# Measure engagement conversion rates
Common Analysis Patterns
- Bottleneck Identification: Find steps with highest drop-off rates
- Segment Comparison: Compare conversion across user groups
- Temporal Analysis: Track conversion over time
- A/B Testing: Compare different funnel variations
- Optimization Impact: Measure changes before/after improvements
Integration Examples
See examples/ directory for:
basic_funnel.py- Simple funnel analysissegmented_funnel.py- Advanced segmentation analysis- Sample datasets for testing
Best Practices
- Ensure data quality and consistency
- Define clear funnel steps
- Consider user journey time windows
- Validate statistical significance
- Focus on actionable insights
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How to use it
Take nicepkg/funnel-analysis from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.