Revenue metrics
Contents
PostHog computes a set of revenue metrics from the revenue data you send us, whether that comes from a payment platform like Stripe or from revenue events. These metrics are exposed through managed views, so you can query them in product analytics insights, the SQL editor, and PostHog AI, so you can build the exact view you need.
Breakdowns
You can break your revenue down by different properties to see what your revenue looks like for each of your individual products, plans, customers, and more. Some common breakdowns include:
- Product name
- Initial coupon
- Customer ID
- Country
- Transaction amount
Because your revenue data is exposed as managed views, you can slice it however you need by querying those views in product analytics insights or the SQL editor.
MRR and ARR
Monthly Recurring Revenue (MRR) is how much money you're making from customers with active subscriptions.
This is automatically calculated by PostHog based on the revenue data you send us. For event sources, the MRR is only included if you configure a revenue event with a subscription property.
When breaking down your data per month, we report what that amount was on the last day of the month.
You can also look at the Annual Run Rate (ARR) instead. This is your current revenue projected out over 12 months (MRR * 12). This number doesn't try to predict what your revenue will be in the future; it assumes you'll keep the exact same customers paying the exact same amount for the next 12 months. It's unlikely to reflect the actual revenue 12 months from now, but it's usually the first number your investors will ask you about.
MRR breakdown
Besides seeing a global overview of your MRR, you can also break it down by the different components that make up your MRR:
| Component | Description |
|---|---|
| New MRR | MRR from new customers |
| Expansion | MRR from existing customers who have paid more in the current subscription period than the previous one |
| Contraction | MRR from existing customers who have paid less in the current subscription period than the previous one |
| Churn | MRR from existing customers who cancel their subscription OR whose charge was 0 in the current subscription period |
This is calculated day by day. If you're looking at a timeframe where we display monthly data then we'll display the aggregated data for the whole month.
Gross revenue
This is all the revenue you made regardless of whether it's a recurring charge or not, including one-time purchases. It will also include negative charges in case you've refunded a customer.
Subscriptions and customers
PostHog also tracks how many active subscriptions and customers you have, regardless of whether they're paying or not, alongside a count of how many customers/subscriptions you're gaining (new customers) or losing (churned customers) in each period.
These will only have meaningful information in case you've configured a subscription property in your revenue data source.
We'll use the number of churned customers to calculate your churn rate # churned_customers / # total customers. This is then used to calculate your LTV.
ARPU
Average Revenue Per User (ARPU) is a measure of how much revenue you're making from each user on average during that period. It's not restricted to subscriptions only and includes all revenue you're making.
LTV
Lifetime Value (LTV) is a measure of how much you should expect to make in revenue from all your customers through their entire lifetime as a customer. This is calculated as ARPU / churn rate.
If you don't have any churn rate we'll not display any datapoints. If you have a churn rate but don't have any revenue then we'll display 0.
Top customers
You can identify your top customers and how much revenue they're generating for you. This uses deferred revenue to calculate the revenue for each customer, which means that if someone's paid a lump sum for a multi-month subscription you'll see it properly split across months if you've set the charge period accordingly in your data source.
For data warehouse sources we'll use the data source identifier. We'll only be able to display the name if you've connected your source to the persons or groups table in the revenue analytics settings.
Using revenue data in product analytics
You can use your revenue data for deeper product analytics insights, too. This allows you to:
- Create custom revenue funnels
- Analyze user journeys that lead to purchases
- Segment users by revenue contribution
When working with revenue data in product analytics, you may want to use the convertCurrency function for accurate reporting across different currencies.
We also expose streamlined views of your revenue data. You can find them under the views tab in our SQL editor.