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PostHog

Analytics

Raw product events sitting in an analytics tool tell a rep nothing until someone connects them to an account. PostHog tracks usage and behaviour across self-serve and PLG motions, and Revenue Labs reads those events into account-level signal, flagging what was used and when activity dropped.

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Website

https://posthog.com

From source record to operating state

01 | The tool on its own

Events become insights, funnels, and trends.

↓

02 | With AI bolted on

PostHog AI answers product questions.

↓

03 | A system that learns

Events enter account state.

The tool alone > AI bolted on > AI-native

What changes when PostHog feeds a system that learns

Three jobs PostHog already does, and what each becomes when its evidence joins live company, contact and deal state.

01 | The tool on its own
02 | With AI bolted on
03 | AI-native
Product analytics
Events become insights, funnels, and trends.
PostHog records product events and turns them into insights, funnels, and trends. Product analysts still choose the event definition and commercial question.
PostHog AI answers product questions.
PostHog AI answers questions from PostHog data. The result stays in PostHog and does not attach the signal to the company or deal outside that stack.
Events enter account state.
PostHog events and insights enter the account record with call, ticket, and stage context.
Session replays
A replay shows what happened before a problem.
Session Replay shows real user interactions, errors, and the surrounding context. A product manager still finds the relevant session and decides what it means.
PostHog AI finds and summarises replays.
Replay summaries help investigate a product issue. They do not attach replay evidence to a company or deal, or update the next deal action.
Replay evidence reaches the deal.
Repeated errors and abandoned paths are resolved to the account, where every capability can read the product signal.
Feature flags and experiments
Flags and experiments control product changes.
PostHog feature flags and experiments let teams target releases and compare results. Product teams still decide which result matters to revenue.
PostHog AI answers experiment questions.
PostHog AI answers questions from PostHog data. The result stays in PostHog and does not compare the experiment with renewal, expansion, or loss outcomes.
Commercial outcomes teach product signal.
Closed outcomes reveal which product changes and behaviours preceded them. Future reviews use the product pattern learned from those outcomes.
Runs on it

Capabilities that act on connected evidence

BUILT FOR SECURITY, CONTROL AND SCALE

Connect data securely, capture every agent's activity, and enforce permissions with ease.

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CERTIFIED + COMPLIANT WITH:

ISO 27001:2022

GDPR

CCPA

Data Protection Act 2018

The GTM teams that learn fastest will win.
Connect your stack to a system that learns.
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