Rank #1 of 4 in Product Analytics
Install
npm install posthog-js
vs Amplitude
vs Mixpanel
vs Plausible AnalyticsShowcase
Verified integrations
Connections to other tracked products — hover a chip for the verbatim evidence quote behind it.
By theme — the product's score on each story themeBy theme
Agenticness — how well agents can access and operate the productAgenticnessevidence →
How well agents can access and operate the product
Automation depth — how much of the product can run unattendedAutomation depthevidence →
How much of the product can run unattended
Dashboards reporting — stories about dashboards reporting in this arenaDashboards reportingevidence →
Stories about dashboards reporting in this arena
Event ingestion — stories about event ingestion in this arenaEvent ingestionevidence →
Stories about event ingestion in this arena
Flags experiments — stories about flags experiments in this arenaFlags experimentsevidence →
Stories about flags experiments in this arena
Funnels retention — stories about funnels retention in this arenaFunnels retentionevidence →
Stories about funnels retention in this arena
Integrations — connecting to other tools — breadth and depth of built-in integrationsIntegrationsevidence →
Connecting to other tools — breadth and depth of built-in integrations
Openness — open source, data portability, and self-hosting storiesOpennessevidence →
Open source, data portability, and self-hosting stories
Privacy cookieless — stories about privacy cookieless in this arenaPrivacy cookielessevidence →
Stories about privacy cookieless in this arena
Privacy posture — data-handling and privacy storiesPrivacy postureevidence →
Data-handling and privacy stories
Session replay — stories about session replay in this arenaSession replayevidence →
Stories about session replay in this arena
Warehouse sql — stories about warehouse sql in this arenaWarehouse sqlevidence →
Stories about warehouse sql in this arena
Story verdicts — every judged story with its evidenceStory verdicts
What’s free: 3 free · 0 paid · 0 enterprise · 32 not stated in evidence
Follow the green: where the map greys out is where PostHog stops today. ✓ full · ~ partial · ! disputed · — none · n/a not applicable.
Agenticness — how well agents can access and operate the productAgenticness
How well agents can access and operate the product
API surface
Drive the product through a documented public API
✓9/10
unlocks → Scoped API keys · Versioning policy · API sandbox
Subscribe to events via webhooks
~4/10
Build against official SDKs
✓7/10
Issue scoped/least-privilege API credentials for an agent
—–
Connect an agent via an official MCP server
✓8/10
Download a machine-readable API spec (OpenAPI or equivalent)
✓9/10
Rely on versioned APIs with a documented deprecation policy
—0/10
Test against a sandbox environment without touching production data
—–
Explore an interactive API reference with runnable examples
~3/10
Docs for agents
Point an agent at llms.txt or agent-oriented docs
✓9/10
Agentic features
Delegate tasks to a built-in AI assistant inside the product
!4/10
Operate the product with natural-language commands
!5/10
Plug MCP servers into this product so it can use their tools
—0/10
Get AI-generated insights and suggestions from my data inside the product
!5/10
Set up automations that run autonomously in the background
~6/10
Automation depth — how much of the product can run unattendedAutomation depth
How much of the product can run unattended
Dashboards reporting — stories about dashboards reporting in this arenaDashboards reporting
Stories about dashboards reporting in this arena
Event ingestion — stories about event ingestion in this arenaEvent ingestion
Stories about event ingestion in this arena
Identity
Flags experiments — stories about flags experiments in this arenaFlags experiments
Stories about flags experiments in this arena
Funnels retention — stories about funnels retention in this arenaFunnels retention
Stories about funnels retention in this arena
Integrations — connecting to other tools — breadth and depth of built-in integrationsIntegrations
Connecting to other tools — breadth and depth of built-in integrations
Openness — open source, data portability, and self-hosting storiesOpenness
Open source, data portability, and self-hosting stories
Privacy cookieless — stories about privacy cookieless in this arenaPrivacy cookieless
Stories about privacy cookieless in this arena
Privacy posture — data-handling and privacy storiesPrivacy posture
Data-handling and privacy stories
Session replay — stories about session replay in this arenaSession replay
Stories about session replay in this arena
Warehouse sql — stories about warehouse sql in this arenaWarehouse sql
Stories about warehouse sql in this arena
Sorted by importance (agentic first) (high → low) · 53/53 stories · click a row’s chevron for the rationale and evidence
Drive the product through a documented public API G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 9/10 | Tprobed | |
Connect an agent via an official MCP server G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 8/10 | Tprobed | |
Delegate tasks to a built-in AI assistant inside the product G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | disputed | 4/10 | Dcontradicted | |
Plug MCP servers into this product so it can use their tools G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | none | 0/10 | ||
Download a machine-readable API spec (OpenAPI or equivalent) G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 9/10 | Tprobed | |
Point an agent at llms.txt or agent-oriented docs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 9/10 | Tprobed | |
Use an official CLI G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 8/10 | Tprobed | |
Build against official SDKs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 7/10 | Tprobed | |
Run the product headlessly / in CI for automation G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 7/10 | Tprobed | |
Set up automations that run autonomously in the background G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 6/10 | Xcommunity | |
Get AI-generated insights and suggestions from my data inside the product G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | disputed | 5/10 | Dcontradicted | |
Operate the product with natural-language commands G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | disputed | 5/10 | Dcontradicted | |
Subscribe to events via webhooks G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 4/10 | Cclaimed | |
Explore an interactive API reference with runnable examples G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 3/10 | Tprobed | |
Rely on versioned APIs with a documented deprecation policy G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | 0/10 | ||
Issue scoped/least-privilege API credentials for an agent G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | untested | none yet | |
Test against a sandbox environment without touching production data G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 1 | none | untested | none yet | |
Query my raw events with SQL (or an SQL-equivalent query language) inside the platform C Raw access | developer | Warehouse sql — stories about warehouse sql in this arenaWarehouse sql | 3 | full | 9/10 | Cclaimed | |
Answer "which activation step loses users?" myself with funnels and drop-off analysis, without an analyst C Self serve insights | founder | Funnels retention — stories about funnels retention in this arenaFunnels retention | 3 | full | 8/10 | Cclaimed | |
Roll out features behind flags targeted by user properties, cohorts, and percentage rollouts C Feature flags | developer | Flags experiments — stories about flags experiments in this arenaFlags experiments | 3 | full | 8/10 | Cclaimed | |
Run A/B experiments with goal metrics and statistical significance reported on the results C Experimentation | product-manager | Flags experiments — stories about flags experiments in this arenaFlags experiments | 3 | full | 8/10 | Cclaimed | |
Run analytical queries and pull raw event data back through a documented query/export API G Raw access | developer | Warehouse sql — stories about warehouse sql in this arenaWarehouse sql | 3 | full | 8/10 | Tprobed | |
Build multi-step funnels with filters and breakdowns to find where users drop off C Behavioral analysis | product-manager | Funnels retention — stories about funnels retention in this arenaFunnels retention | 3 | full | 7/10 | Cclaimed | |
Define rules that trigger actions automatically on events G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 3 | full | 7/10 | Cclaimed | |
Measure retention over time and slice it by behavioral cohorts C Behavioral analysis | product-manager | Funnels retention — stories about funnels retention in this arenaFunnels retention | 3 | full | 7/10 | Cclaimed | |
Send events from web, mobile, and backend apps through official SDKs for the major languages and platforms G Instrumentation | developer | Event ingestion — stories about event ingestion in this arenaEvent ingestion | 3 | full | 7/10 | Xcommunity | |
Export all of my data in open formats and leave G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | partial | 6/10 | Tprobed | |
Have an agent build a dashboard of my key metrics end-to-end via the API or MCP server C Ai analytics ops | ai-native user | Dashboards reporting — stories about dashboards reporting in this arenaDashboards reporting | 3 | partial | 6/10 | Tprobed | |
Have an agent answer growth questions from live product data by running queries through the API or MCP server C Ai analytics ops | ai-native user | Warehouse sql — stories about warehouse sql in this arenaWarehouse sql | 3 | disputed | 5/10 | Dcontradicted | |
Self-host the core product G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | disputedfree | 5/10 | Dcontradicted | |
Watch recordings of real user sessions with sensitive input masked by default C Replay | product-manager | Session replay — stories about session replay in this arenaSession replay | 3 | none | 0/10 | ||
Prevent my data from being used to train AI models G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 3 | none | untested | none yet | |
Read the product's source under an open license G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 2 | fullfree | 9/10 | Cclaimed | |
Compose saved insights into shareable dashboards for my team C Dashboards | product-manager | Dashboards reporting — stories about dashboards reporting in this arenaDashboards reporting | 2 | full | 8/10 | Cclaimed | |
Stream events onward to third-party destinations (CRM, ad platforms, webhooks) from the analytics platform G Destinations | developer | Integrations — connecting to other tools — breadth and depth of built-in integrationsIntegrations | 2 | full | 8/10 | Cclaimed | |
Sync events between the platform and my own data warehouse (query warehouse tables in-product or export events continuously to it) G Warehouse | developer | Warehouse sql — stories about warehouse sql in this arenaWarehouse sql | 2 | full | 8/10 | Cclaimed | |
Do everything through the API that I can do in the UI G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 2 | full | 7/10 | Tprobed | |
Explore the paths users actually take before or after a key event C Behavioral analysis | product-manager | Funnels retention — stories about funnels retention in this arenaFunnels retention | 2 | full | 7/10 | Cclaimed | |
Have an agent create, target, and toggle feature flags through the API or MCP server C Ai analytics ops | ai-native user | Flags experiments — stories about flags experiments in this arenaFlags experiments | 2 | partial | 6/10 | Tprobed | |
Jump from a funnel drop-off or an error event straight to session replays of the affected users C Replay | product-manager | Session replay — stories about session replay in this arenaSession replay | 2 | partial | 6/10 | Cclaimed | |
Schedule recurring jobs or workflows G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 2 | partial | 5/10 | Cclaimed | |
Analyze behavior at the account or company level, not just per user, for B2B products C Behavioral analysis | product-manager | Funnels retention — stories about funnels retention in this arenaFunnels retention | 2 | partial | 4/10 | Cclaimed | |
Create and manage dashboards and saved insights programmatically via the API C Dashboards | developer | Dashboards reporting — stories about dashboards reporting in this arenaDashboards reporting | 2 | partial | 4/10 | Tprobed | |
Perform bulk operations across many items at once G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 2 | partial | 4/10 | Xcommunity | |
Capture clicks, pageviews, and form interactions automatically without writing tracking code for each event C Instrumentation | product-manager | Event ingestion — stories about event ingestion in this arenaEvent ingestion | 2 | none | 0/10 | ||
Choose where my data is stored (region/residency) G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | nonefree | 0/10 | ||
Control data retention and deletion G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | untested | none yet | |
Identify users across devices and merge anonymous pre-signup activity into their identified profile C Identity | developer | Event ingestion — stories about event ingestion in this arenaEvent ingestion | 2 | none | untested | none yet | |
Opt out of telemetry and usage tracking G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | untested | none yet | |
Track product usage without third-party cookies so I can minimize or avoid cookie consent banners C Privacy first analytics | founder | Privacy cookieless — stories about privacy cookieless in this arenaPrivacy cookieless | 2 | none | untested | none yet | |
Subscribe to dashboards and get alerted when a key metric moves abnormally C Dashboards | product-manager | Dashboards reporting — stories about dashboards reporting in this arenaDashboards reporting | 1 | full | 7/10 | Cclaimed | |
Bulk-import historical events from another analytics tool or a data export into the platform G Identity | developer | Event ingestion — stories about event ingestion in this arenaEvent ingestion | 1 | partial | 3/10 | Xcommunity | |
Version, review, and roll back my automations G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 1 | none | untested | none yet |
Opportunities — the stories that would move this product's scores, from its own judged verdictsOpportunitiestop 8 of 25 stories with headroom
What would move PostHog’s scores — derived from its own judged verdicts, biggest headroom first. Each line quotes what the judge found missing; shipping it (or evidencing it publicly) is the fix.
Agenticness — how well agents can access and operate the productPlug MCP servers into this product so it can use their tools
nonemoves agent-readyimpact 45
All MCP-related evidence describes PostHog exposing its own MCP server so external AI clients/editors (Claude, Cursor, etc.) can query PostHog's data and tools — the reverse direction of this story.
Privacy posture — data-handling and privacy storiesPrevent my data from being used to train AI models
nonemoves PA Scoreimpact 30
No evidence in the pack addresses AI-training data opt-out or any privacy control preventing customer data from being used to train AI models; nothing in the docs or community items mentions this capability.
Session replay — stories about session replay in this arenaWatch recordings of real user sessions with sensitive input masked by default
nonemoves PA Scoreimpact 30
Missing: any documentation of input masking/privacy defaults, evidence of what is masked or how, and confirmation it's on by default rather than opt-in.
Agenticness — how well agents can access and operate the productIssue scoped/least-privilege API credentials for an agent
nonemoves agent-readyimpact 30
No evidence describes scoped or least-privilege API key/credential issuance for agents — the API docs mention basic HTTP event capture and an OpenAPI spec exists, but nothing about permission scoping, token minting with restricted access, or credential management for AI agents specifically.
Agenticness — how well agents can access and operate the productRely on versioned APIs with a documented deprecation policy
nonemoves API qualityimpact 30
There is an OpenAPI spec probe (posthog-probe-3) confirming an API exists, but no evidence anywhere in the pack of API versioning scheme or a documented deprecation policy for that API.
Agenticness — how well agents can access and operate the productExplore an interactive API reference with runnable examples
partialq3/10moves API qualityimpact 21
Missing: confirmation of an interactive API console, runnable code snippets, or live 'try it' functionality in the docs.
Event ingestion — stories about event ingestion in this arenaCapture clicks, pageviews, and form interactions automatically without writing tracking code for each event
nonemoves PA Scoreimpact 20
Missing: any documented autocapture feature, evidence of automatic click/pageview/form tracking, or an example of a PM enabling capture with zero code.
Privacy cookieless — stories about privacy cookieless in this arenaTrack product usage without third-party cookies so I can minimize or avoid cookie consent banners
nonemoves PA Scoreimpact 20
The evidence pack contains no mention of cookie-based vs cookieless tracking, consent banners, or privacy-compliant capture configuration—only general analytics, session replay, and SDK/API capture details.
Showing the top 8 of 25 — every none/partial verdict in the story verdicts table is headroom.
Think a verdict is wrong? Every verdicts-table row has a Flag link — see the methodology.
Coverage map — which docs area, API section, or community source covers which judged storiesCoverage map7 surfaces · 40 covered stories
Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.
docs40 stories
- Point an agent at llms.txt or agent-oriented docs
- Run the product headlessly / in CI for automation
- Connect an agent via an official MCP server
- Use an official CLI
- Drive the product through a documented public API
- Build against official SDKs
- Subscribe to events via webhooks
- Get AI-generated insights and suggestions from my data inside the product
- Set up automations that run autonomously in the background
- Delegate tasks to a built-in AI assistant inside the product
- Operate the product with natural-language commands
- Explore an interactive API reference with runnable examples
- Download a machine-readable API spec (OpenAPI or equivalent)
- Perform bulk operations across many items at once
- Define rules that trigger actions automatically on events
- Schedule recurring jobs or workflows
- Have an agent build a dashboard of my key metrics end-to-end via the API or MCP server
- Create and manage dashboards and saved insights programmatically via the API
- Compose saved insights into shareable dashboards for my team
- Subscribe to dashboards and get alerted when a key metric moves abnormally
- Bulk-import historical events from another analytics tool or a data export into the platform
- Send events from web, mobile, and backend apps through official SDKs for the major languages and platforms
- Have an agent create, target, and toggle feature flags through the API or MCP server
- Run A/B experiments with goal metrics and statistical significance reported on the results
- Roll out features behind flags targeted by user properties, cohorts, and percentage rollouts
- Build multi-step funnels with filters and breakdowns to find where users drop off
- Analyze behavior at the account or company level, not just per user, for B2B products
- Measure retention over time and slice it by behavioral cohorts
- Explore the paths users actually take before or after a key event
- Answer "which activation step loses users?" myself with funnels and drop-off analysis, without an analyst
- Stream events onward to third-party destinations (CRM, ad platforms, webhooks) from the analytics platform
- Do everything through the API that I can do in the UI
- Export all of my data in open formats and leave
- Read the product's source under an open license
- Self-host the core product
- Jump from a funnel drop-off or an error event straight to session replays of the affected users
- Have an agent answer growth questions from live product data by running queries through the API or MCP server
- Run analytical queries and pull raw event data back through a documented query/export API
- Query my raw events with SQL (or an SQL-equivalent query language) inside the platform
- Sync events between the platform and my own data warehouse (query warehouse tables in-product or export events continuously to it)
OpenAPI spec11 stories
- Run the product headlessly / in CI for automation
- Drive the product through a documented public API
- Build against official SDKs
- Explore an interactive API reference with runnable examples
- Download a machine-readable API spec (OpenAPI or equivalent)
- Have an agent build a dashboard of my key metrics end-to-end via the API or MCP server
- Create and manage dashboards and saved insights programmatically via the API
- Have an agent create, target, and toggle feature flags through the API or MCP server
- Do everything through the API that I can do in the UI
- Export all of my data in open formats and leave
- Run analytical queries and pull raw event data back through a documented query/export API
Hacker News11 stories
- Build against official SDKs
- Get AI-generated insights and suggestions from my data inside the product
- Set up automations that run autonomously in the background
- Delegate tasks to a built-in AI assistant inside the product
- Operate the product with natural-language commands
- Perform bulk operations across many items at once
- Have an agent build a dashboard of my key metrics end-to-end via the API or MCP server
- Bulk-import historical events from another analytics tool or a data export into the platform
- Send events from web, mobile, and backend apps through official SDKs for the major languages and platforms
- Self-host the core product
- Have an agent answer growth questions from live product data by running queries through the API or MCP server
GitHub README8 stories
- Connect an agent via an official MCP server
- Build against official SDKs
- Subscribe to events via webhooks
- Get AI-generated insights and suggestions from my data inside the product
- Set up automations that run autonomously in the background
- Delegate tasks to a built-in AI assistant inside the product
- Define rules that trigger actions automatically on events
- Schedule recurring jobs or workflows
Cdp docs4 stories
llms.txt2 stories
Claims vs evidence — vendor claims reconciled against independent verdictsClaims vs evidence
7 of 25 testable claims verified · 5 contradicted → integrity 0/100
31 distinct capability claims found in PostHog’s own claimed-docs/GitHub materials, reconciled against our judge’s independent verdicts.
7
Verified
13
Unverified
5
Contradicted
15
Undersold
Verified (8)
“Capture custom events with attached properties from any official SDK”
Send events from web, mobile, and backend apps through official SDKs for the major languages and platformsfullproof ↗
“Capture events via HTTP from any language that can send requests”
Drive the product through a documented public APIfullproof ↗
“Run trends, funnels, retention, and SQL queries from any MCP client or AI editor”
“Steer the whole product from Slack, web, desktop app, or your editor via MCP”
“Turn product-data signals (errors, rage clicks, failed queries) into researched reports and reviewable pull requests”
Set up automations that run autonomously in the backgroundpartialproof ↗
“Use plain-text prompts to ship a feature flag, debug a stack trace, or run a HogQL query via Claude”
Have an agent create, target, and toggle feature flags through the API or MCP serverpartialproof ↗
“Official CLI for using PostHog from terminal, coding agents, scripts, and CI/CD”
“Official CLI for using PostHog from terminal, coding agents, scripts, and CI/CD”
Run the product headlessly / in CI for automationfullproof ↗
Unverified (20)
“Build insights, assemble into dashboards, share them, and set alerts on key metrics”
Compose saved insights into shareable dashboards for my teamfullproof ↗
“Build insights, assemble into dashboards, share them, and set alerts on key metrics”
Subscribe to dashboards and get alerted when a key metric moves abnormallyfullproof ↗
“Wrap a change behind a feature flag, gradually roll it out, and disable it instantly without redeploying”
Roll out features behind flags targeted by user properties, cohorts, and percentage rolloutsfullproof ↗
“Target flag rollouts by person property, cohort, or group, then view replays/events/exceptions from affected users”
Roll out features behind flags targeted by user properties, cohorts, and percentage rolloutsfullproof ↗
“Target flag rollouts by person property, cohort, or group, then view replays/events/exceptions from affected users”
Jump from a funnel drop-off or an error event straight to session replays of the affected userspartialproof ↗
“Run A/B experiments with automatic randomization, exposure tracking, and Bayesian or frequentist statistics”
Run A/B experiments with goal metrics and statistical significance reported on the resultsfullproof ↗
“Query, manage, and modify data throughout the product using SQL”
Query my raw events with SQL (or an SQL-equivalent query language) inside the platformfullproof ↗
“Sync Stripe, Postgres, Salesforce, HubSpot, and other sources to query alongside product data in one SQL query”
Sync events between the platform and my own data warehouse (query warehouse tables in-product or export events continuously to it)fullproof ↗
“Ingest data from existing tools, filter/reshape events during ingestion, and route results onward in realtime or on a schedule”
Stream events onward to third-party destinations (CRM, ad platforms, webhooks) from the analytics platformfullproof ↗
“Free self-hosted deployment via Docker Compose under MIT license”
“Build trends, funnels, retention, paths, stickiness, and lifecycle insights on captured events”
Build multi-step funnels with filters and breakdowns to find where users drop offfullproof ↗
“Build trends, funnels, retention, paths, stickiness, and lifecycle insights on captured events”
Measure retention over time and slice it by behavioral cohortsfullproof ↗
“Build trends, funnels, retention, paths, stickiness, and lifecycle insights on captured events”
Explore the paths users actually take before or after a key eventfullproof ↗
“Run SQL insights directly with SELECT, FROM, JOIN, WHERE, GROUP BY”
Query my raw events with SQL (or an SQL-equivalent query language) inside the platformfullproof ↗
“Create workflows that automate actions or send messages to users”
Define rules that trigger actions automatically on eventsfullproof ↗
“Combine all data in a context warehouse queryable directly by users, agents, or dashboards”
Sync events between the platform and my own data warehouse (query warehouse tables in-product or export events continuously to it)fullproof ↗
“Define experiment variants and target metrics, with automatic randomization and stats reporting”
Run A/B experiments with goal metrics and statistical significance reported on the resultsfullproof ↗
“Save insights to dashboards, share them, and get alerted when metrics move”
Compose saved insights into shareable dashboards for my teamfullproof ↗
“Save insights to dashboards, share them, and get alerted when metrics move”
Subscribe to dashboards and get alerted when a key metric moves abnormallyfullproof ↗
“Configure ingestion pipelines from templates, custom code, or have PostHog AI write the function”
Define rules that trigger actions automatically on eventsfullproof ↗
Contradicted (8)
“Run trends, funnels, retention, and SQL queries from any MCP client or AI editor”
Have an agent answer growth questions from live product data by running queries through the API or MCP serverdisputedproof ↗
“Session replay plays back real user sessions with a synced DevTools panel showing console logs, network requests, and errors”
Watch recordings of real user sessions with sensitive input masked by defaultnoneproof ↗
“Agent pulls stack trace, error message, and metadata to propose a code fix for a crash”
Get AI-generated insights and suggestions from my data inside the productdisputedproof ↗
“Free self-hosted deployment via Docker Compose under MIT license”
“Turn product-data signals (errors, rage clicks, failed queries) into researched reports and reviewable pull requests”
Get AI-generated insights and suggestions from my data inside the productdisputedproof ↗
“Use plain-text prompts to ship a feature flag, debug a stack trace, or run a HogQL query via Claude”
Operate the product with natural-language commandsdisputedproof ↗
“Watch real user session replays to diagnose issues and understand behavior”
Watch recordings of real user sessions with sensitive input masked by defaultnoneproof ↗
“Configure ingestion pipelines from templates, custom code, or have PostHog AI write the function”
Get AI-generated insights and suggestions from my data inside the productdisputedproof ↗
Undersold (15)
Point an agent at llms.txt or agent-oriented docsfullproof ↗
Explore an interactive API reference with runnable examplespartialproof ↗
Download a machine-readable API spec (OpenAPI or equivalent)fullproof ↗
Perform bulk operations across many items at oncepartialproof ↗
Have an agent build a dashboard of my key metrics end-to-end via the API or MCP serverpartialproof ↗
Create and manage dashboards and saved insights programmatically via the APIpartialproof ↗
Bulk-import historical events from another analytics tool or a data export into the platformpartialproof ↗
Analyze behavior at the account or company level, not just per user, for B2B productspartialproof ↗
Answer "which activation step loses users?" myself with funnels and drop-off analysis, without an analystfullproof ↗
Do everything through the API that I can do in the UIfullproof ↗
Export all of my data in open formats and leavepartialproof ↗
Run analytical queries and pull raw event data back through a documented query/export APIfullproof ↗
Claims outside our story set (6)
Real capability claims found in PostHog’s own materials, but no story in this arena’s taxonomy covers them yet — that’s feedback on the taxonomy, not a mark against the product.
“Inject and upload source maps for error tracking”
source ↗“Track errors, receive alerts, and resolve issues to improve the product”
source ↗“No-code survey templates plus a custom survey builder”
source ↗“GA-like dashboard for monitoring web traffic, sessions, conversion, web vitals, and revenue”
source ↗“Capture traces, generations, latency, and cost for LLM-powered apps”
source ↗“AI observability captures traces, generations, latency, and cost for LLM apps”
source ↗
Business model
Open-source core with a generous monthly free tier per product (1M events, 5K replays); paid usage-based pricing per event/replay/flag request beyond that, enterprise add-ons custom.
pricing ↗Score trend
How this product’s scores have moved as evidence and verdicts are re-derived — a point per change, not per day.
Flag
⚑ Flag a verdictThink a verdict is wrong? Opens a prefilled GitHub issue — or use the ⚑ next to any verdict above.
For agents
Agent surface uptime llms.txt 100% · openapi.json 100% (30d, checked every 6h since Sep 8 '26)