ARPPU

Average Proceeds Revenue Per Paying User. Measures the average proceeds revenue generated from paying users. This includes revenue from subscriptions and non-renewing purchases, associated with the A/B tested paywall.

This is a cohort metric, meaning it is calculated by fetching the users who were distributed to the relevant variation of the experiment within the selected dates.

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Advanced Usage Tip

You can view advanced variations data in the ARRPU chart, with Experiment Variations filter.

Go to ARPPU chart, click on [Where] filter, select Experiment Variations and choose your experiment's variation.

ARPU

Average Proceeds Revenue Per User. Measures the average proceeds revenue generated from all users. This includes revenue from subscriptions and non-renewing purchases, associated with the A/B tested paywall.

This is a cohort metric, meaning it is calculated by fetching the users who were distributed to the relevant variation of the experiment within the selected dates.

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Advanced Usage Tip

You can view advanced variations data in the Cumulative LTV chart, with Experiment Variations filter.

Go to Cumulative LTV chart, click on [Where] filter, select Experiment Variations and choose your experiment's variation.

ARPAS

Average Revenue Per Active Subscriber. Measures the average revenue generated from active subscribers, including both paying and free-trial users. This includes revenue from subscriptions and non-renewing purchases, associated with the A/B tested paywall.

This is a cohort metric, meaning it is calculated by fetching the users who were distributed to the relevant variation of the experiment within the selected dates.

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Advanced Usage Tip

You can view advanced variations data in the ARPAS chart, with Experiment Variations filter.

Go to ARPAS chart, click on [Where] filter, select Experiment Variations and choose your experiment's variation.

View to Action

Conversion rate from viewing a paywall to performing a valuable action, which includes the start of a free trial, the start of a paid subscription, or a non-renewing purchase, regardless of possible future refunds.

Developers must send the "Paywall Shown" event from the SDK; otherwise, the conversion will not be available.

This is a cohort metric, meaning it is calculated by dividing the number of purchase or free-trial start events by the number of unique paywall views within the selected dates.

View to Trial

Conversion rate from viewing a paywall to the start of a free trial.

Developers must send the "Paywall Shown" event from the SDK; otherwise, the conversion will not be available.

This is a cohort metric, meaning it is calculated by dividing the number of free-trial start events by the number of unique paywall views within the selected dates.

View to Purchase

Conversion rate from viewing a paywall to a first paid event, which includes the start of a paid subscription, a conversion of a free-trial subscription, or a non-renewing purchase, regardless of possible future refunds.

Developers must send the "Paywall Shown" event from the SDK; otherwise, the conversion will not be available.

This is a cohort metric, meaning it is calculated by dividing the number of first paid events by the number of unique paywall views within the selected dates.

Trial Conversion

Conversion rate from the start of a free trial to a paid subscription, regardless of possible future refunds.

This is a cohort metric, meaning it is calculated by dividing the number of free-trial conversion events by the number of free-trial start events that occurred within the selected dates.

Sales

Total amount billed to customers, excluding refunded transactions and revenue that is not associated with the A/B tested paywall.

This is a non-cohort metric, meaning it is calculated by summing up the sales within the selected dates.

Proceeds

Estimated revenue developer receives after deducting taxes, store commission and refunded transactions. Excludes the revenue that is not associated with the A/B tested paywall.

This is a non-cohort metric, meaning it is calculated by summing up the proceeds within the selected dates.

Refunds

Total amount of refunds associated with the A/B tested paywall.

This is a non-cohort metric, meaning it is calculated by summing up the refunds within the selected dates.

Trials

The number of free-trial start events.

This is a non-cohort metric, meaning it is calculated by counting the free-trial events within the selected dates.

Unique Purchases

The number of first paid events, which includes the start of a paid subscription, the conversion of a free-trial subscription, or a non-renewing purchase, regardless of possible future refunds.

This is a non-cohort metric, meaning it is calculated by counting the first paid events within the selected dates.

Unique Views

The number of unique users who viewed a paywall from the variation. Developers must send the "Paywall Shown" event from the SDK; otherwise, the metric will not be available.

This is a non-cohort metric, meaning it is calculated by counting the Unique Views within the selected dates.

Views

The number of Paywall Views, where every repetitive view is counted.
Developers must send the "Paywall Shown" event from the SDK; otherwise, the metric will not be available.

This is a non-cohort metric, meaning it is calculated by counting the Paywall Views within the selected dates.

Users

The number of users who were distributed to the relevant variation of the experiment.

This is a non-cohort metric, meaning it is calculated by counting the users within the selected dates.

pARPU 1Y

Predicted Average Revenue Per User after the 1st year. This metric uses machine learning to predict the ARPU that might be achieved after the 1st year since purchase. It takes into account the current revenue trends and user behavior to provide an estimate of future revenue.
This is a cohort metric, meaning it is calculated by fetching the users who were distributed to the relevant variation of the experiment within the selected dates.

Learn more about Experiment Predictions.

pARPPU 1Y

Predicted Average Revenue Per Paying User after the 1st year. This metric uses machine learning to predict the ARPPU that might be achieved after the 1st year since purchase. It takes into account the current revenue trends and user behavior to provide an estimate of future revenue.
This is a cohort metric, meaning it is calculated by fetching the users who were distributed to the relevant variation of the experiment within the selected dates.

Learn more about Experiment Predictions.

pARPAS 1Y

Predicted Average Proceeds Revenue Per Any Subscriber after the 1st year. This metric uses machine learning to predict the ARPAS that might be achieved after the 1st year since purchase. It takes into account the current revenue trends and user behavior to provide an estimate of future revenue.
This is a cohort metric, meaning it is calculated by fetching the users who were distributed to the relevant variation of the experiment within the selected dates.

Learn more about Experiment Predictions.

pProceeds 1Y

Predicted Average Proceeds Revenue Per User after the 1st year. This metric uses machine learning to predict the ARPU that might be achieved after the 1st year since purchase. It takes into account the current revenue trends and user behavior to provide an estimate of future revenue.
This is a cohort metric, meaning it is calculated by fetching the users who were distributed to the relevant variation of the experiment within the selected dates.

Learn more about Experiment Predictions.