analytics-product

Analyze product analytics data to define event taxonomies, funnels, cohorts, and retention metrics.

Updated Mar 27, 2026
One-click install
npx skills add https://github.com/CenredJun/openclaw-claudecode-setup-kit --skill analytics-product-cenredjun
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: analytics-product
Source: https://github.com/CenredJun/openclaw-claudecode-setup-kit/tree/main/skills/analytics-product
Command: npx skills add https://github.com/CenredJun/openclaw-claudecode-setup-kit --skill analytics-product-cenredjun

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps product teams turn raw event data into actionable product metrics by defining a clear event taxonomy, building funnels, measuring cohort retention, calculating A/B significance, and selecting a north star metric to guide product decisions.

Core Features & Use Cases

  • Event Taxonomy & Tracking: Recommend snake_case event names, essential properties, and a consistent taxonomy for PostHog or Mixpanel.
  • Funnel & Cohort Analysis: Build activation and conversion funnels, compute weekly cohort retention matrices, and benchmark retention for voice and conversational products.
  • Experimentation & Dashboards: Run statistical significance checks for A/B tests, evaluate feature flags, and produce north-star and product dashboards.
  • Use Case: Audit a startup's PostHog events to identify where users drop out of the activation funnel, run cohort retention for the last 8 weeks, and recommend three prioritized experiments to improve week-1 retention.

Quick Start

Ask the skill to audit your PostHog event taxonomy, calculate 8-week cohort retention, and propose a north star metric with recommended dashboard KPIs.

Frequently Asked Questions about analytics-product

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

FAQPage Schema
How do I calculate cohort retention using product analytics data from PostHog?

You can calculate cohort retention by processing event-level exports with standard Python and Pandas. The skill computes weekly cohort retention matrices and benchmarks retention specifically for voice and conversational products.

What is the best way to run A/B test significance evaluation for product features?

The best way to run A/B test significance evaluation is by applying statistical calculations to your feature flag data. The skill evaluates feature flags and performs statistical significance checks to validate product experiments.

How do I define an event taxonomy with consistent snake_case event names for Mixpanel?

To define an event taxonomy for Mixpanel, establish consistent snake_case event names and essential properties. The skill audits your tracking setup and recommends a clear taxonomy to ensure accurate funnel analysis.

Can I use Python and Pandas to build activation funnels from raw event tracking data?

Yes, you can use Python and Pandas to build activation funnels from raw event tracking data. The skill processes event-level exports to identify where users drop out of the conversion funnel.

How do I select a north star metric to guide product dashboard setup?

To select a north star metric, analyze your product analytics data to find a guiding indicator for decisions. The skill proposes a north star metric and recommends dashboard KPIs based on your event taxonomy.