PostHog
https://posthog.com1
Events
4
Articles
1
Entities
3
Facts
2
Relations
Competitors (6)
Profile
The open source Product OS for building successful products
PostHog is an all-in-one product and data toolkit designed specifically for product engineers. It provides a single platform for analytics, session replay, feature flags, experiments, surveys, and a data warehouse, eliminating the need for fragmented data stacks. Built on an open-source core, PostHog prioritizes transparency and developer-friendly, usage-based pricing. The company differentiates itself through a 'Product OS' philosophy, where 10+ integrated products work from a single source of truth. By avoiding traditional sales-led growth in favor of product-led reputation, PostHog has achieved significant scale, serving over 190,000 teams and 65% of YC batches. PostHog operates as a 'default alive' company with zero intention of selling, aiming for an IPO to maintain its independence. Recent developments include the launch of PostHog AI, Web Analytics, and a managed Data Warehouse, positioning it as a comprehensive alternative to point solutions like Amplitude or Mixpanel.
Social Profiles
Product Portfolio
PostHog is positioning itself as a comprehensive 'Product OS' for engineers, replacing multiple siloed tools (Mixpanel, FullStory, LaunchDarkly, Segment) with a single, integrated data stack and application layer.
Product & User Analytics
Understanding user behavior and conversion
- Product Analytics — The core suite for event tracking, funnel analysis, and user retention.
- Web Analytics — Privacy-first, lightweight analytics for website traffic and performance.
- LLM Analytics — Specialized tracking for AI-powered applications, monitoring costs, and performance.
User Experience & Feedback
Observing and gathering qualitative user data
- Session Replay — Full visual recordings of user sessions with console logs and network monitoring.
- Surveys — In-app prompts to gather direct user feedback and NPS scores.
- Error Tracking — Identify and triage exceptions and bugs directly within user sessions.
Ship & Experiment
Managing product releases and A/B testing
- Feature Flags — Toggle features on/off for specific user segments without deploying code.
- Experiments — Run statistically rigorous A/B/n tests to validate product changes.
Data Infrastructure
Managing the underlying data stack and storage
- Data Warehouse — Managed ClickHouse-based storage for all customer and business data.
- Data Pipelines — Connect and sync data between PostHog and 120+ external sources/destinations.
- Workflows — Automate messaging and internal actions based on user events.
Atomic Events (1)
PostHog Launches Mobile Session Replay
PostHog introduced session replay support for mobile platforms including iOS, Android, React Native, and Flutter.
Extracted Entities (1)
| Type | Name | Confidence | Last Seen |
|---|---|---|---|
| pricing_plan | Free Tier | 0% | Mar 31, 2026 |
Facts (3)
| Entity | Field | Value | Previous | Change | Observed |
|---|---|---|---|---|---|
| PostHog | employees | 193 | — | — | Mar 31, 2026 |
| PostHog | customers | 190,000+ | — | — | Mar 31, 2026 |
| Product Analytics | price_usd | 0.00005 | — | — | Mar 31, 2026 |
Intelligent Briefs (2)
How is PostHog expanding its mobile capabilities?
PostHog officially launched Mobile Session Replay for iOS, Android, React Native, and Flutter on March 27. This move completes their 'Product OS' vision by bringing high-fidelity visual debugging (console logs, network monitoring, rage taps) to mobile apps, positioning them as a direct, more affordable competitor to mobile-first tools like UXCam and LogRocket. Action: Highlight PostHog's all-in-one advantage to customers currently paying for separate web and mobile analytics tools.
What is PostHog's current scale and momentum?
As of March 2026, PostHog has reached over 190,000 teams and is used by 65% of YC batches. The company is 'default alive' (profitable) with a team of 193 'misfits'. Their strategy of avoiding traditional sales in favor of developer-led growth is succeeding, evidenced by their reaching significant scale without a massive sales force. Action: Monitor their 'Data Warehouse' adoption, as it signals a move from simple analytics to being the primary data store for startups.