product-data-analyst

Analyze product usage data to produce structured markdown reports with recommendations.

6|1|Updated Mar 5, 2026
One-click install
npx skills add https://github.com/pwv-vc/agentcribs-community --skill product-data-analyst
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: product-data-analyst
Source: https://github.com/pwv-vc/agentcribs-community/tree/main/resources/tearsheets/arsenal/dot-claude/skills/product-data-analyst
Command: npx skills add https://github.com/pwv-vc/agentcribs-community --skill product-data-analyst

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Product teams often struggle to translate raw usage data into clear, actionable insights about funnels, engagement, and relationship signals. This skill provides a structured framework to analyze product data and generate concrete recommendations that improve onboarding, activation, and user satisfaction.

Core Features & Use Cases

  • Unified analytics for funnels, engagement, reactions, and trends.
  • Guidance on when to use product analytics vs sql-reader, with practical examples.
  • Real-world scenario: diagnose onboarding and activation bottlenecks, compare power-user vs casual-user patterns, and surface actionable recommendations.

Quick Start

Identify a concrete product question for this session and describe the time range to analyze, then run the corresponding workflow to generate a structured insights report.

Frequently Asked Questions about product-data-analyst

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

FAQPage Schema
How do I analyze product data to find onboarding and activation bottlenecks?

To analyze onboarding and activation bottlenecks, you examine product usage data to reveal patterns in funnels and engagement. This process surfaces actionable recommendations by comparing power-user and casual-user behaviors within a specified time range.

What is the best way to turn raw product usage data into actionable insights?

Turning raw product usage data into actionable insights requires applying a structured analytics framework to identify patterns in funnels, engagement, and relationship signals. This approach outputs structured markdown reports containing metrics, examples, and recommended actions.

Do I need a canonical data model to analyze product funnels and engagement?

Yes, analyzing product funnels and engagement requires a canonical data model structured around messages, conversations, and enrichment. This underlying data structure is necessary to accurately reveal relationship signals and produce actionable recommendations.

How do I generate structured reports for product data analysis?

You generate structured markdown reports for product data analysis by running a workflow against a defined product question and time range. The resulting report includes specific metrics, real-world examples, and recommended actions based on usage patterns.

When should I use product analytics versus sql-reader for investigating reaction trends?

Use product analytics for reaction-trend investigations when you need to surface actionable recommendations from engagement patterns and relationship signals. Use sql-reader for direct database queries when raw data extraction is required without structured analytical frameworks.