Product analytics? PostHog does that.

Funnels, path analysis, trend charts, retention graphs, and more

Product analytics

We’re tracking how users engage with our platform, where they fall out of our funnels and what the overall trends in behavior are. The data we’ve gathered has helped us make several important decisions about where to improve our platform.

Tiffany Wong

Co-founder, Pry


Find drop-off across a series of actions

  • Filtering

    Set filters for individual steps – or the entire funnel – by user 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

Visualize user data with graphs, tables, charts, maps, and more

  • Trends

    Plot any event over time, such as a feature being used. You can even do math and multiple series

  • Advanced filtering

    Apply however many filters you need to or breakdown by any event, user or group property with advanced logic

  • Breakdown tables

    Break out your trends by any event property

  • Querying

    Speed up long running queries across large datasets in one click, if you want to

User paths

Set start and end points to see how users navigate your product, website, or conversion funnel

  • Step insights

    See who dropped off at each step, who did or didn’t complete a step, and the drop-off rate

  • Wildcard groups

    Group similar steps into a mega-step (where any of a group of events can trigger a step)

  • Exclusion events

    Prevent specific events from appearing in a path

  • Granular controls

    Visualize any sequence of page views, screen views or events, with up to 20 steps

Correlation analysis

When analyzing funnels, correlation analysis highlights significant events or properties that may be useful in determining how likely someone is to converting or churning.

More insight types

Retention, stickiness, and lifecycle views

  • Retention

    See how many users return on subsequent days after first visiting your site or product

  • Stickiness

    Learn how many times users perform a specific event in a period of time

  • Lifecycle

    Discover how your active users break down, highlighting those who have recently stopped being active or those who have just become active for the first time


  • Dashboard filtering

    Filter saved insights on a dashboard by anything - event properties, user properties, cohorts - even if a feature flag was active during a user’s session

  • Embeddable dashboards with auto-refresh

    Embed a dashboard iframe and always have near-realtime data - great for showing KPIs on a TV

  • Weekly updates by Slack or email

    Send dashboard updates to a Slack channel or to colleagues via email at any recurring frequency

  • Access restrictions

    Limit dashboard access with role-based permissions or using private projects

  • Customizable layouts

    Configure how many insights appear per row or column

    • Autocapture

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

    • Data visualization

      Filter data by user 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

PostHog vs...

How does PostHog Product analytics compare?

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 user property
Breakdown by user 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 user property
Include and exclude Wildcards
Exclusion events
Hide repeating steps
Regex for path cleaning
Max number of steps50120+102020
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 / Integrations70+50+40+40+50+

Blog posts that mention Product analytics


Here's what the Product Analytics Team is building next.

  • Data table exploration

    We're building an insights-like search functionality for everything qualitative. That means people, recordings, cohorts, events, and groups. This will enable you to search using simple sentences to easily find anything in PostHog. Additionally, you can trigger context-sensitive actions - such as creating cohorts from results.


The product analytics team

Here are the people bringing you product analytics.

Shockingly, this team prefers their pizza without pineapple

  • Marius Andra

    Team lead

    Software Engineer

  • Michael Matloka

    Software Engineer

  • Yakko Majuri

    Software Engineer

  • Paul D'Ambra

    Software Engineer

  • Luke Harries

    Head of Product

  • Thomas Obermüller

    Software Engineer

Learn more about this team

Try PostHog

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PostHog does that.

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