Skill UI

This comprehensive workflow guides developers through implementing full-stack product analytics using PostHog. It covers key areas including defining event taxonomies, capturing user actions (client-side), identifying and updating user properties, and performing B2B group analytics. It also demonstrates server-side event tracking using posthog-node, ensuring a complete, accurate, and traceable view of user behavior and product usage across web, mobile, and API sources.

This skill provides advanced techniques for optimizing PostHog Cloud usage and reducing associated costs. It covers auditing event volume, implementing intelligent event sampling (e.g., sampling pageviews or autocapture events), filtering bot traffic, and tuning session recording rates. The goal is to maintain critical analytical value while staying within budget limits.

This guide provides minimal working examples demonstrating the three core PostHog functionalities: event capture, user identification, and feature flag evaluation. It covers both server-side (Node.js, Python) and client-side (JavaScript) SDK usage, as well as direct API calls, making it perfect for initial integration setup, testing, and learning basic product analytics patterns.

This comprehensive guide outlines the process of migrating analytics data from major platforms like Google Analytics, Mixpanel, Amplitude, or Segment to PostHog. It covers implementing a dual-write strategy, mapping historical event names and properties, and performing bulk historical data imports, ensuring a smooth transition and data continuity.

This comprehensive guide outlines advanced strategies for optimizing PostHog in production environments. Key techniques covered include implementing local feature flag evaluation to eliminate network latency, optimizing event batching for network efficiency, utilizing strategic event sampling, and writing efficient HogQL queries. Master these methods to dramatically improve data collection reliability and query speed.

This skill guides you through integrating PostHog's Customer Data Platform (CDP) features. It covers setting up webhooks to trigger real-time actions (e.g., syncing to CRM, sending notifications) when specific user events occur. Furthermore, it demonstrates how to query event data using the Events API and perform complex funnel analysis using HogQL, allowing for deep, custom insights into user behavior.

A comprehensive guide to product analytics, covering essential concepts like event tracking (PostHog, Mixpanel), funnels, cohort analysis, retention metrics, North Star Metrics, and OKR setting. Use this skill to define data-driven product strategies, optimize user journeys, and build robust performance dashboards.

A powerful toolset for automating core PostHog product analytics tasks via Rube MCP. It enables developers and analysts to capture user events, list and filter event data, manage feature flags (creation, retrieval, listing), and inspect user profiles. Ideal for integrating advanced product tracking and A/B testing workflows directly into development pipelines.

A comprehensive guide to product analytics, covering event tracking, funnels, cohort retention, north star metrics, OKRs, and dashboards. Examples include PostHog implementation and Python code for retention analysis. Ideal for product managers and data analysts seeking data-driven decisions.

A powerful toolset for automating core PostHog product analytics tasks via Rube MCP. It enables developers and analysts to capture user events, list and filter event data, manage feature flags (creation, retrieval, listing), and inspect user profiles. Ideal for integrating advanced product tracking and A/B testing workflows directly into development pipelines.