Active Customers Chart
Available in Charts v3 only. This chart isn't listed when Charts v3 isn't enabled.
The Active Customers chart measures the number of customers seen in a given period. In RevenueCat, the term "customer" refers to the person using an app, regardless of whether they have yet made a purchase.
This chart provides a view of your total active customer base over time, including both new and returning customers. You can use our conversion charts to measure the portion of these customers that then start trials, convert to paid, etc.
Available settings
- Filters: Yes
- Segments: Yes
How to use Active Customers in your business
This chart should be used to track the total number of customers engaging with your app over time, which reflects your overall customer base size and activity levels, filtered or segmented by the dimensions that are most important to your business to understand which segments are most actively using your app.
For example, if you notice changes in your conversion rates or subscription revenue, you can analyze your active customer volume by segment to understand if the composition of your active customer base has shifted. Similarly, comparing Active Customers to New Customers over time can reveal whether growth is driven by new customer acquisition or improved retention of existing customers.
Calculation
For each period we count:
- Active Customers: The approximate number of unique customers for whom RevenueCat recorded SDK activity during the period.
Data is only accurate for the last 28 days. Data before that may be inaccurate or zero.
FAQs
| Question | Answer |
|---|---|
| Why might Active Customers differ from active users reported by other analytics platforms? | Each platform has different definitions and measurement methods. RevenueCat counts a customer as active when it records SDK activity for them during the period. Other platforms might use different activity signals like app opens, screen views, or custom events. Additionally, if your app initializes the RevenueCat SDK conditionally or after certain customer actions, this may cause differences in counts. This chart also uses a fast algorithm to determine unique customers, which can lead to small discrepancies for customers with very large active customer bases. |
| How does customer aliasing affect this metric? | After App User IDs are aliased, those IDs are treated as the same customer when RevenueCat sees them again. If RevenueCat saw both IDs before the alias, they may still be counted separately until those records fall outside the chart's data window. |