What visualization libraries does this skill use?

The skill primarily utilizes Plotly for interactive charts, but it also supports Matplotlib and Seaborn for professional static visualizations.

Does it provide suggestions for improvement?

Yes, beyond just showing the data, the skill helps identify the largest drop-off points and suggests potential optimization strategies to fix those bottlenecks.

Is this skill only applicable to e-commerce?

No, while excellent for e-commerce, it is equally effective for SaaS onboarding, mobile app engagement analysis, and sales pipeline tracking.

What data do I need for this skill to work?

You need user journey data containing unique user identifiers, timestamps, and specific action labels such as page views, clicks, or completed steps.

Can this skill compare different user segments?

Yes, it supports deep segmentation analysis, allowing you to compare conversion rates across categories like device type, geography, or marketing source.

Funnel Analysis

Name: Funnel Analysis
Author: liangdabiao

byliangdabiao

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데이터 과학 및 ML

Analyzes multi-step user conversion journeys to identify bottlenecks and optimize business growth metrics.

소개

The Funnel Analysis skill empowers users to transform raw behavioral data into actionable growth insights by mapping step-by-step conversion journeys. It automates the process of calculating drop-off rates, performing demographic or behavioral segmentation, and generating interactive visualizations to pinpoint exactly where users exit a process. Whether you are optimizing an e-commerce checkout flow, a user registration sequence, or a complex marketing campaign, this skill provides the analytical framework and statistical rigor needed to improve retention and maximize conversion efficiency.

주요 기능

Multi-step conversion rate calculation and visualization
Automated bottleneck and drop-off point identification
78 GitHub stars
Generation of actionable business optimization recommendations
Advanced user segmentation by attributes like device or location
Interactive data visualization using Plotly and Seaborn

사용 사례

Optimizing e-commerce checkout flows from product view to final purchase
Evaluating marketing campaign performance across different acquisition channels
Analyzing user onboarding sequences to improve sign-up completion rates

소개

주요 기능

Multi-step conversion rate calculation and visualization
Automated bottleneck and drop-off point identification
78 GitHub stars
Generation of actionable business optimization recommendations
Advanced user segmentation by attributes like device or location
Interactive data visualization using Plotly and Seaborn

사용 사례

Optimizing e-commerce checkout flows from product view to final purchase
Evaluating marketing campaign performance across different acquisition channels
Analyzing user onboarding sequences to improve sign-up completion rates