Charts v3 (Beta)

Overview of the key changes & improvements of our new Charts v3 beta

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We’re excited to welcome you to the beta of our new Charts v3. We've rebuilt charts to give you faster, more flexible insights, including:

• Real-time reporting on almost all charts
• A new unified subscription model for consistent reporting across stores
• Improved definitions for existing dimensions like Platform and Country
• New dimensions to filter and segment by, including Custom Attributes & Ad Attribution
• Brand new charts for Trial Conversion Rate and Active Customers, with more for Paywall metrics coming soon

⚠️Supported stores

At this time we support App Store, Play Store, Stripe and RevenueCat Web Billing apps in Charts v3. Support for Amazon, Roku, and Paddle is coming soon.

📘Feedback

As you explore the beta and have feedback or questions about the experience, please let us know here.

Getting Started

You can access Charts v3 from your dashboard by toggling Charts v3 on in Charts. Look for the real-time icon next to supported Charts. To see the current version of each chart, simply toggle Charts v3 off.

Summary of changes

New features

• Charts are now updated in real-time as events occur Learn more
• New filters & segments for deeper analysis Learn more
• A new Trial Conversion Rate chart for measuring that rate by trial start date cohorts, and segmenting it for more granular analysis Learn more
• Period-over-Period comparisons to track performance changes across time periods Learn more

Improvements

• Charts are now defined from a consistent subscription definition that is universal across stores, and allows us to distinctly measure cases like a Product Change or a Resubscription separately from a standard Renewal. Learn more
• Refunded transactions no longer cause metrics like Revenue, Conversion to Paying, etc. to change retroactively for complete periods. Instead, transactions that are later refunded are included by default in all charts, and their revenue or conversion (if applicable) is subtracted on the date the refund actually happened. Learn more
• The Platform dimension now reports a customer's first seen platform, not their last seen platform, to make analyzing acquisition channels easier and to avoid customer dimensions changing over time.
• The Country dimensions now reports the country associated with a customer's app store account (if available), or IP-based location otherwise.
• The current Trial Conversion chart (renamed to the Trial Conversion Funnel) included any future payment on an App Store subscription as a conversion to paid, even if that conversion did not come from the trial start. Now, only conversions to paid from the trial start are included in this chart.
• The cohorting methodology for the Cohort Explorer and Prediction Explorer has been updated to ensure all customers in larger cohorts are given equal time to mature when reporting performance in each period. Learn more

Detailed changes

Real-time reporting

Previously, charts refreshed every 2 to 12 hours depending on the dataset. Now, almost all charts update in real-time, providing:

• Immediate insights into app performance
• Improved intra-day monitoring for launches, experiments, or spikes
• More consistent data across charts

You can now make faster, more informed decisions without waiting for batch updates.

Improved subscription definition

Our new Charts v3 are now modeled on our Subscriptions entity, which normalizes the various store-specific behaviors down to a common set of definitions that can be measured across stores, and have consistent events created for them.

You can learn more about the subscription data model here.

Impact

As a result of that change, you'll see some differences in the data our Charts v3 provide.

Change	Description	Impact
Product changes create new subscriptions	When a subscriber changes from one product (A) to another (B), we treat their first subscription to product A as expired, and create a second subscription to product B.	In charts like New Paid Subscriptions and Active Subscriptions Movement, this results in the count of new subscriptions and churned subscriptions increasing by equal amounts. Other charts like Subscription Retention already treated product changes like new subscriptions, and therefore the count of new subscriptions in a given period should more closely align between these charts.
Resubscriptions create new subscriptions	When a subscriber starts a subscription after a previous App Store subscription has lapsed, we consider it to be a resubscription, not a renewal on their prior subscription.	In charts like Trial Conversion, payments that would have previously counted as conversions to paid from the original trial start which were actually resubscriptions from a later time are no longer included in the chart. In addition, charts such as New Paid Subscriptions and Active Subscriptions Movement now have new subscriptions and churned subscriptions increasing by equal amounts to account for resubscriptions. Subscription Retention now has an increase in subscriptions, and a proportional decrease in retention for any resubscriptions that were otherwise counted as renewals of prior subscriptions.

Refund behavior

When a payment is refunded, it will be deducted from revenue and conversion (if applicable) on the day the refund occurs. Here's how that will impact various chart types:

• Revenue: A purchase will add revenue on the day it occurs. If it's later refunded, it will subtract revenue on the day the refund occurs.
• Conversion: An applicable purchase will be counted as a conversion in each of the timeframes it is applicable to (e.g. a conversion on day 5 of a customer's lifecycle is included in the 7 days timeframe, 14 days, etc). If it's later refunded, the conversion will be removed in each of the timeframes the refund is applicable to (e.g. a refund on day 10 of a customer's lifecycle results in the conversion being removed from the 14 days timeframe, 30 days, etc; but would not effect the 7 days timeframe, since the refund occurred after that timeframe was completed).
• Lifetime value (LTV): An applicable purchase's revenue will be included in each of the timeframes it is applicable to (e.g. a purchase on day 5 of a customer's lifecycle is included in the 7 days timeframe, 14 days, etc). If it's later refunded, the revenue will be removed in each of the timeframes the refund is applicable to (e.g. a refund on day 10 of a customer's lifecycle results in the revenue being removed from the 14 days timeframe, 30 days, etc; but would not effect the 7 days timeframe, since the refund occurred after that timeframe was completed).

Cohorting methodology of Cohort Explorer and Prediction Explorer

The cohorting methodology for the Cohort Explorer and Prediction Explorer has been updated to calculate each daily cohort's periods, and then sum them for cohorts larger than daily, whereas previously larger cohorts (weekly, monthly, etc.) had their periods defined by the first and last day of the cohort (e.g. Day 1 and Day 30 of a given month), regardless of when an individual customer was first seen within that timeframe, resulting in some customers who were first seen later in a period having their revenue pushed out to the next period.

Example Scenario

January monthly cohort with two customers:

• Customer A joins January 2nd, makes $10 purchase on January 31st (their day 29)
• Customer B joins January 28th, makes $10 purchase on February 4th (their day 7)

Old behavior:

• Day 0-30 revenue: Only $10 (Customer A's purchase on calendar day 31 of January)
• Day 31-60 revenue: $10 (Customer B's purchase, even though it was only their day 7)

New behavior:

• Day 0-30 revenue: $20 (both purchases within 30 days of each customer's start)
• Day 31-60 revenue: $0 (no purchases in this timeframe for either customer)

New and updated dimensions

We've introduced new dimensions for filtering & segmenting, with more coming soon, and have made important updates to existing dimensions to make them more useful.

New dimensions

1. Experiment: Filter & segment charts by the experiment & variant that a customer was enrolled in
2. App version: Filter & segment charts by the first seen app version of a customer to understand how metrics like conversion rate are impacted by app version
3. Custom attributes: Filter & segment charts by the latest custom attribute values you've set for a customer, to understand how different segments of your audience behave.
4. Attribution: Filter & segment charts by the attribution data you send to RevenueCat such as Source, Campaign, Keyword, etc. Some ad attribution integrations such as Apple Search Ads automatically send this data to RevenueCat once enabled, and all ad attribution integrations support optionally sending it through the reserved attributes for ad attribution. Learn more here.
5. Paywall: Filter & segment charts by the RevenueCat Paywall that a purchase was made from.

Updated dimensions

1. Platform: Now refers to the first seen platform of a customer, not their last seen platform, so that metrics like conversion rates and LTV can be segmented by the platform a customer originated on without it changing over time (e.g. if a customer converts on the web and then downloads your iOS app)
2. Country: Now prioritizes the app store country of a customer or purchase over the customer's IP-based location. In charts which measure purchases, like Active Subscriptions, the app store storefront that the purchase occurred in will be used as the country; while in charts that measure customer cohorts, like Initial Conversion or Realized LTV per Customer, the first seen app store country of the customer will be used.

Period-over-Period comparisons

You can now compare chart data against the previous period to identify trends and measure changes in performance.

How it works

• Enable comparisons using the Compare dropdown to compare against the previous period, which uses the same time period length as your selected date range
• The chart displays both the current period and comparison period as separate lines
• The summary shows the total for the selected period and the percentage change from the comparison period
• Hover over any data point to see the percentage change compared to the previous period at that point in time

Supported charts

• Active Subscriptions
• Active Trials
• ARR
• Churn
• Conversion to Paying
• Initial Conversion
• MRR
• New Customers
• New Trials
• Non-subscription Purchases
• Realized LTV per Customer
• Realized LTV per Paying Customer
• Refund Rate

New charts

Available now

1. Trial Conversion Rate: A new chart to measure the number of trials that started in a given period, and the portion of them that converted to paying customers, so that you can understand how likelihood to pay changes over time and by various dimensions. This differs from the Trial Conversion Funnel in that (1) it is cohorted by trial start date, and (2) focuses just on the conversion from trial to paid, and is therefore segmentable by other dimensions the way our other conversion charts are as well.
2. Active Customers: A new chart to measure the number of unique customers who were active each day in your app. A "customer" is any user of your app, regardless of whether they've made a purchase, and includes both new customers and existing customers.

Coming soon

Paywall conversion, LTV, and abandonment charts for measuring performance of each of your RevenueCat Paywalls.

Upcoming changes & improvements

• Charts v3 support App Store & Play Store apps, with additional store support currently in development.
• Paywall conversion, LTV, and abandonment charts for RevenueCat Paywalls

Unsupported charts

Nearly all charts support the real-time system, with the exception of:

• Prediction Explorer
• App Store Refund Requests
• Play Store Cancel Reasons
• Customer Center Survey Responses

We'll look to migrate these charts to support real-time reporting in the future as well.