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.