{"id":482083,"date":"2026-07-31T21:52:00","date_gmt":"2026-07-31T21:52:00","guid":{"rendered":"https:\/\/userpilot.com\/blog\/posthog-features\/"},"modified":"2026-08-01T22:19:45","modified_gmt":"2026-08-01T22:19:45","slug":"posthog-features","status":"publish","type":"post","link":"https:\/\/userpilot.com\/blog\/posthog-features\/","title":{"rendered":"PostHog Features in 2026: What’s Free, What’s Cloud-Only, and What Changed"},"content":{"rendered":"

PostHog features can look considerably cheaper on the pricing page than they do in articles about the platform. I ran PostHog’s calculator for 10 million anonymous events and got roughly $324 per month. The $1,080 figure still circulating is off by a wide margin, and getting it wrong can throw off your product analytics<\/a> budget at scale.<\/p>\n

Several new features have landed since PostHog’s early reviews: CUPED, holdout groups, mobile session replay, and mobile surveys, adding to an already broad set of product tools. Even with that wider toolkit, your team still has to configure, maintain, and use those features effectively.<\/p>\n

I’ll explain what PostHog’s open-source model requires from your team, examine how far its analytics, experimentation, and qualitative research tools go, and break down its current pricing with realistic usage examples.<\/p>\n

\n\n\n\n\n\n\n\n\n\n\n\n
Product area<\/th>\nWhat it includes<\/th>\nWhat teams use it for<\/th>\n<\/tr>\n<\/thead>\n
Product and web analytics<\/td>\nFunnels, trends, retention, paths, cohorts, lifecycle reports, dashboards, autocapture, group analytics, and website metrics.<\/td>\nUnderstanding how users and accounts discover, adopt, and return to the product.<\/td>\n<\/tr>\n
Session replay and heatmaps<\/td>\nWeb and mobile recordings, console logs, network activity, replay filters, privacy controls, AI summaries, and click or scroll heatmaps.<\/td>\nInvestigating the sessions behind funnel drop-offs, errors, and confusing user behavior.<\/td>\n<\/tr>\n
Feature flags and experiments<\/td>\nBoolean and multivariate flags, gradual rollouts, kill switches, A\/B tests, holdouts, redirect tests, and no-code website experiments.<\/td>\nReleasing changes safely and measuring whether they improve the target behavior.<\/td>\n<\/tr>\n
Surveys and workflows<\/td>\nIn-app surveys, NPS and CSAT templates, conditional questions, email workflows, audience splits, delays, and campaign experiments.<\/td>\nCollecting feedback and automating messages based on product behavior.<\/td>\n<\/tr>\n
Engineering observability<\/td>\nError tracking, stack traces, issue grouping, releases, logs, distributed traces, AI and LLM monitoring, and replay linked to errors.<\/td>\nDiagnosing technical failures and connecting the user experience to the underlying issue.<\/td>\n<\/tr>\n
Data infrastructure<\/td>\nData warehouse connections, SQL and HogQL, transformations, batch exports, real-time destinations, webhooks, and query endpoints.<\/td>\nCombining PostHog data with the wider company data stack and sending it to other systems.<\/td>\n<\/tr>\n
AI and developer tools<\/td>\nPostHog AI, natural-language queries, replay summaries, SQL generation, MCP, CLI tools, and AI-assisted setup and debugging.<\/td>\nQuerying PostHog data and managing parts of the platform from AI assistants or developer environments.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

The breadth is one of PostHog\u2019s main advantages, especially for technical teams that want to keep analytics, experimentation, and engineering data in one ecosystem. However, most products have their own usage limits and pricing dimensions, so adopting more of the platform can make both implementation and cost management more demanding.
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\n\"demo<\/a><\/p>\n

What is PostHog, and what does its open-source label mean?<\/h2>\n

PostHog is an open-source developer platform that helps product and engineering teams understand user behavior and build, test, and improve digital products. It combines product and web analytics, session replay, feature flags, experiments, and event tracking into a single platform, reducing the need to stitch together separate tools. The wider suite also includes a data warehouse, data pipelines, error tracking, and AI observability. These products share the same underlying data stack, though certain capabilities and managed services are available only through PostHog Cloud.<\/p>\n

Instead of PostHog Cloud, you can choose self-hosting, which means running the repository on your own infrastructure and requires specific advanced capabilities within each product. For example, when you self-host surveys, you lose multi-question logic, custom HTML, and event-based triggers.<\/p>\n

In practice, self-hosting means everything runs on a single machine, and a self-hosted PostHog is unlikely to scale beyond a couple hundred thousand events without significant engineering effort. PostHog even recommends Cloud for most companies.<\/p>\n

When you run the open-source version, you take on:<\/p>\n