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funnel-analysis

Analyze multi-step funnels to compute conversion rates and identify bottlenecks.

264|45|Updated Dec 24, 2025
Search Tags:#onboarding#analytics#optimization#visualization#conversion#segmentation#funnel
One-click install
npx skills add https://github.com/liangdabiao/claude-data-analysis-ultra-main --skill funnel-analysis-liangdabiao
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: funnel-analysis
Source: https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/funnel-analysis
Command: npx skills add https://github.com/liangdabiao/claude-data-analysis-ultra-main --skill funnel-analysis-liangdabiao

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, plotly, matplotlib, seaborn, and includes scripts (resource) components.

What problem does it solve?

This Skill helps you analyze multi-step user journeys, compute conversion rates, and identify bottlenecks across funnels in marketing, e-commerce, onboarding, and content workflows. It enables segmentation, interactive visualizations, and actionable insights to optimize conversions and reduce friction.

Core Features & Use Cases

  • Multi-step Funnel Construction: Build funnels from event data or step indicators and define the exact sequence.
  • Conversion Rate Analysis: Calculate step-by-step and overall conversion rates with clear interpretation.
  • Segmentation & Visualization: Compare funnels across different user attributes and view interactive charts.
  • Automated Insights: Generate practical recommendations to optimize funnels and increase yield.
  • Use Cases: E-commerce purchase funnel, onboarding activation, content engagement funnels, and lead-nurturing processes.

Quick Start

Load your data, define the funnel steps (e.g., Homepage → Search → Product View → Add to Cart → Purchase), run the funnel analysis, and generate interactive charts and a detailed report. For example:

  • Prepare data with boolean step indicators or timestamps
  • Run the funnel analyzer, set steps, and build the funnel
  • View results and export visualizations and insights

Frequently Asked Questions about funnel-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze conversion funnels to identify where users drop off?▼

Conversion funnel analysis computes step-by-step drop-off rates across user journeys. Define your sequence (e.g., signup → activation → purchase), load event data with pandas, calculate conversion rates between steps, and visualize bottlenecks with plotly or matplotlib to pinpoint optimization targets.

Can I segment funnel performance by user attributes like cohorts or regions?▼

Yes. Segment funnels by any user attribute in your dataset—cohort, region, device type—using pandas grouping. Compare conversion rates across segments with seaborn visualizations to identify which groups experience higher friction and where to focus optimization efforts.

What data format do I need to run funnel analysis?▼

Prepare data with either boolean step indicators (user completed step yes/no) or timestamps for each funnel step. Load into pandas DataFrames, ensure user IDs and step sequences are present, then pass to the funnel analyzer to construct and measure conversion paths.

How do I automate funnel reports and share insights with stakeholders?▼

The Skill generates automated reports with step-wise conversion rates, bottleneck summaries, and actionable optimization recommendations. Export interactive visualizations via plotly and structured data via pandas to communicate findings and drive cross-functional decisions.

Does funnel analysis work for multi-stage workflows like onboarding or lead nurturing?▼

Yes. Funnel analysis applies to any multi-step journey—onboarding flows, lead-gen pipelines, content engagement, e-commerce purchases. Define steps in sequence, measure progression rates, and segment by user properties to optimize activation, conversion, and retention at each stage.

What limitations should I know before applying funnel analysis to my data?▼

Funnel analysis assumes sequential, ordered steps. It requires complete event tracking and consistent user identifiers; missing data or out-of-order events can distort rates. For highly nonlinear user paths or real-time streaming data, consider preprocessing steps or alternative approaches.

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