Product analytics

Product analytics with autocapture

PostHog is the only product analytics platform built to natively work with session replay, feature flags, A/B testing, and surveys.

Screenshot of PostHog Product Analytics
  • gathers 30% more data than with Google Analytics

    "We could autocapture... events using the JS snippet and... configure custom events."

    Read the story
  • improved conversion rates by 10-20%

    "we observed drop-offs at very particular stages of our onboarding flow."

    Read the story
  • increased registrations by 30%

    "From [funnels], we could easily jump to session replays to see the drop-off point."

    Read the story
  • manages features and developer relations

    " view of conversion rates and user paths, without... extra setup time."

    Read the story


Find drop-off across a series of actions

  • Filtering

    Set filters for individual steps – or the entire funnel – by person property, group or cohort, or event property

  • Graph types

    Track user progression between steps, conversion time between each step, and how a funnel’s conversion rate changes over time

  • Step ordering

    Choose between a sequential series of steps, a strict order, or any order of steps that lead to conversion

  • Granular controls

    Set conversion window limit, add exclusionary steps, set attribution type, and see the relative conversion rate between each step

  • Autocapture

    Add PostHog.js to your website or web app to track all event data and retroactively define events

  • Data visualization

    Filter data by person property, group data, and use formulas in queries

  • SQL

    Use PostHog’s filtering interface or switch into SQL mode for more powerful querying

  • Dashboards and insight subscriptions

    Share insights with teams, and get updates when results change

  • Group analytics

    Analyze how any group of people (like an organization) use your product

  • AI engineering

    Integrate with existing monitoring tools and track latency, cost, and model performance

Answer all of these questions (and more) with PostHog Product analytics.

Usage-based pricing

Use product analytics free. Or enter a credit card for advanced features. Either way, your first 1,000,000 events are free – every month.


No credit card required

All other plans

All features, no limitations





Graphs & trends
User paths


Insight & dashboard subscriptions
Not included
Advanced paths
Not included
Correlation analysis
Not included
Not included
Data retention

1 year

7 years

Person profiles
Group analytics
Data pipelines

Monthly pricing

First 1 million events
1-2 million
2-15 million
15-50 million
50-100 million
100-250 million
250 million+


PostHog vs...

Conversion funnels
Historical trends
Time to convert insights
Sequential step order
Strict step order
Any step order
Exclusion events
Conversion windows
Reveal user paths between steps
Anomaly detection
Filter internal and test users
Filter by cohort
Filter by person property
Breakdown by person property
Correlation analysis
Path analysis
Reveal paths from a start point
Reveal paths from an end point
Reveal paths between points
Reveal paths within funnels
Zoom in/out
Define number of users on path
Track pageviews
Track custom events
Filter internal and test users
Filter by cohort
Filter by events or person property
Include and exclude Wildcards
Exclusion events
Hide repeating steps
Regex for path cleaning
Max number of steps
User-level permissions
Project-level permissions
Dashboard-level permissions
Share dashboards externally
Embed dashboards anywhere
Subscribe to dashboards
Pinned dashboards
Dashboard & insight tags
Private insights
Apps / integrations

So, what's best for you?

Reasons a competitor might be better for you (for now...)

  • Time-based analysis for web analytics (e.g. time on page)
  • Natural language processing for creating insights
  • Predictive analytics for extrapolating events into the future
  • Alerting for when events move beyond set thresholds

Reasons to choose

  • Linking between analytics and other features, so you can jump from a graph to a relevant recording
  • Wide range of insight types for analyzing data
  • Formula mode and SQL access to enable deeper analysis
  • Automatic correlation analysis to find significant events
  • Group analytics for teams with B2B customers

Have questions about PostHog?
Ask the community or book a demo.

Featured tutorials

Visit the tutorials section for more.

  • How to calculate and lower churn rate

    In this tutorial, we will calculate and visualize the churn rate then use PostHog’s features of session recordings, cohorts, and actions to lower it.

    Read more
  • How to filter and breakdown arrays with HogQL

    Arrays (AKA lists) are a useful way to store multiple values related to each other under the same key. PostHog's HogQL expressions unlock the ability to make full use of them.

    Read more
  • Calculate bounce rate

    Bounce rate is the percentage of users who leave your page immediately after visiting. It is a popular marketing metric showing the relevance and engagement of content for site visitors.

    Read more
  • How to calculate DAU/MAU ratio

    The ratio of daily active users over monthly active users shows what percentage of your users are active and use your product every day.

    Read more

Install & customize

Here are some ways you can fine tune how you implement product analytics.

Explore the docs

Get a more technical overview of how everything works in our docs.

Meet the team

PostHog works in small teams. The Product Analytics team is responsible for building product analytics.

Roadmap & changelog

Here’s what the team is up to.

Latest update

Jun 2024

Loading bar and longer runtimes for insights and dashboards

Building on the work we did at our Mykonos hackathon, we've now added a new loading bar which reflects the query's process. For longer-running queries which take more than 20s to complete we'll also show the disk, memory, and CPU usage too.

Speaking of longer-running queries, we've also increased the limitations on how long queries can run for. It's not a common occurrence but if you're building a really complex insight and crunching a lot of data then your queries can now run for up to 10 minutes before they'll time out. The same is also true for dashboards!

Up next


See more questions (or ask your own!) in our community forums.

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