Product analytics with autocapture
gathers 30% more data than with Google Analytics
"We could autocapture... events using the JS snippet and... configure custom events."
improved conversion rates by 10-20%
"we observed drop-offs at very particular stages of our onboarding flow."
increased registrations by 30%
"From [funnels], we could easily jump to session replays to see the drop-off point."
manages features and developer relations
"...top-to-bottom view of conversion rates and user paths, without... extra setup time."
Find drop-off across a series of actions
Set filters for individual steps – or the entire funnel – by user property, group or cohort, or event property
Track user progression between steps, conversion time between each step, and how a funnel’s conversion rate changes over time
Choose between a sequential series of steps, a strict order, or any order of steps that lead to conversion
Set conversion window limit, add exclusionary steps, set attribution type, and see the relative conversion rate between each step
AutocaptureAdd PostHog.js to your website or web app to track all event data and retroactively define events
Data visualizationFilter data by user property, group data, and use formulas in queries
SQLUse PostHog’s filtering interface or switch into SQL mode for more powerful querying
Dashboards and insight subscriptionsShare insights with teams, and get updates when results change
Group analyticsAnalyze how any group of people (like an organization) use your product
Answer all of these questions (and more) with PostHog Product Analytics.
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 features, no limitations
Graphs & trends
Insight & dashboard subscriptions
Tags & text cards
First 1 million events
250 million +
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)
- (We're working on this!)
- 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
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.
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.
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.
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.
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.
Query debugger added
We've added a query debugger to PostHog. It isn't strictly intended for external use and is somewhat hidden, but we're announcing it anyway because we love transparency.
The query debugger is only available directly via
app.posthog.com/debug and enables you to run HogQL queries and compare run times. It also generates the ClickHouse SQL version of the query alongside the HogQL version, and offers a breakdown of where time is spent.
Internally, we'll use this to debug queries and find opportunities to improve how HogQL works. For everyone else, it's just there if you want to indulge your curiosity.
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.
- Concept: Universal search for people / recordings / cohorts / events / groups
- feat(product-analytics): Data Exploration view
- RFC: Data exploration
See more questions (or ask your own!) in our community forums.
- Question / TopicRepliesCreated
PostHog products are natively designed to be interoperable using Product OS.
Jump into a playlist of session recordings directly from any point in a graph, or segment of a funnel
See which feature flags were enabled for a user during a session
Filter data down to users within an active experiment, whether part of a control group or a test variant
This is the call to action.
If nothing else has sold you on PostHog, hopefully these classic marketing tactics will.