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carlvellotti
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start-2-2

Analyze product funnels, ROI scenarios, and A/B test results.

13|4|Updated May 28, 2026
Search Tags:#experiment analysis#funnel analysis#product analysis#data-driven decision making#ROI estimation
One-click install
npx skills add https://github.com/carlvellotti/codex-pm-course --skill start-2-2
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: start-2-2
Source: https://github.com/carlvellotti/codex-pm-course/tree/main/.agents/skills/start-2-2
Command: npx skills add https://github.com/carlvellotti/codex-pm-course --skill start-2-2

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires csv, python, pandas, numpy, matplotlib, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a comprehensive toolkit for analyzing product data, from funnel analysis to ROI scenarios and experiment readouts, helping you make informed product decisions.

Core Features & Use Cases

  • Funnel Analysis: Evaluate the activation funnel to identify drop-off points and user problems.
  • ROI Scenarios: Estimate the potential impact and ROI of new features before development.
  • Experiment Readouts: Analyze A/B test results to inform feature decisions and improvements.
  • Use Case: Imagine you've implemented a new feature and want to understand its impact. Use this Skill to analyze the funnel data, estimate the ROI, and analyze the A/B test results to determine the feature's success.

Quick Start

/start 1 1

Frequently Asked Questions about start-2-2

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

FAQPage Schema
How do I run funnel analysis on product data using Python and pandas?▼

Funnel analysis with Python and pandas evaluates activation funnels to identify drop-off points. Process CSV data to map user stages, quantify conversion rates, and pinpoint where users disengage.

How do I estimate ROI and impact for new product features before development?▼

ROI estimation models potential impact before development. Apply business modeling techniques to project scenarios, estimate returns, and validate whether new features justify engineering investment.

How do I analyze A/B test experiment readouts to inform product decisions?▼

Experiment readout analysis evaluates A/B test results to inform feature decisions. Apply statistical testing to CSV data to determine significance, measure impact, and guide data-driven decision making.

Do I need specific CSV data assets to perform product analysis and experiment readouts?▼

Yes, executing product analysis requires specific CSV data assets. The workflow depends on the Codex PM Course data and assets to perform funnel evaluation, ROI estimation, and experiment readout analysis.

What is the best way to visualize experiment analysis results for product decisions?▼

Visualize experiment analysis results using matplotlib to generate charts from pandas DataFrames. Plot funnel conversion rates, ROI scenarios, and A/B test distributions to communicate data-driven product decisions.

Can I use numpy for statistical testing in product experiment readouts?▼

Yes, use numpy for statistical testing in experiment readouts. Calculate significance levels, variance, and distributions to analyze A/B test results and support data-driven product decision making.

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