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Charts

This guide describes all available charts.

MONEY

MRR

MRR (Monthly Recurring Revenue) represents recurring proceeds revenue normalized to a monthly amount. It is calculated as the sum of the monthly fees paid by each paying customer, after deducting the respective app store's commission (Apple or Google Play).
For example, if you have 10 customers each paying $10 per month, the MRR will be calculated as follows:
MRR = 10 subscribers × $10 per month - 30% (or 15%) commission = $70.

All non-monthly subscription plans are normalized to a monthly equivalent. For instance, an annual subscription costing $120 per year will be normalized to $10 per month.

MRR Movement

Cohorts: No.

Monthly Recurring Revenue (MRR) and Annual Recurring Revenue (ARR) movement charts are essential tools for tracking the performance of subscription-based businesses. These charts visualize the growth, contraction, and other changes in recurring revenue over time, providing insights into the financial health and trajectory of a company.

MRR Movement consists of New MRR and Churned MRR.

New MRR is new subscriptions, reactivations and upgrades. In other words, this is everything, that adds the new recurrent revenue.

Churned MRR is a lost recurring revenue from expired subscriptions, downgrades. This is everything, that deducts from the recurrent revenue.

MRR/ARR movement charts are critical for understanding the dynamics of recurring revenue in a subscription-based business model. By breaking down revenue changes into their constituent parts, companies can gain valuable insights into their growth drivers and potential areas of concern. This leads to better-informed strategic decisions and helps in optimizing revenue streams.

ARR

Cohorts: No.

ARR is recurring proceeds revenue normalized in to an annual amount. It's calculated as a sum of the yearly fee paid by each paying customer with a deduction of Apple commission.

ARR Movement

Cohorts: No.

As described above, ARR Movement is pretty the same as MRR Movement Chart. The main difference is that it's calculated as ANNUAL recurring revenue (not monthly). In fact, you can roughly consider ARR = MRR * 12.

ARR Movement consists of new ARR and churned ARR. The logic here is identical to new MRR and churned MRR.


Gross revenue

Cohorts: No.

Gross revenue is a total amount billed to customers for purchasing subscriptions prior to refunds, taxes and Apple’s commission.

Sales

Cohorts: No.

Total amount billed to customers for purchasing in-app purchases. Sales = Gross Revenue - Refunds.

Proceeds

Cohorts: No.

Estimated revenue developer receives after deducting Store commission and VAT.

Refunds

Refunds amount during selected period. This includes both refunds through Customer Care and refunds during subscription upgrade with partial refund.

Refund Rate

Cohorts: No.

The percentage of the total transactions that were completely refunded during a period of time.

Formula is the following:

Refund Rate = Refunded Transactions / All Transactions by the Period * 100%

ARPU

Cohorts: Yes.

APRU is Average Revenue Per User.

Calculated on a cohort basis. The cohort is users, that have installed the app within the selected period. They can be segmented and filtered by country, products, marketing campaigns (depending on what was selected in segments and filters).

We calculate ARPU for the users’ lifetime. This means that ARPU for the given cohort will be calculated by dividing the summarized users' revenue by the total number of users who have installed the app within the selected time frame.

You can choose whether to calculate ARPU using Sales or Proceeds.

Calculate users by events

User created – count all new users in the selected cohort for ARPU calculation.

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Note

For example, we have 100 new users created within the selected period. These users have paid $10 by now. ARPU is equal to $10 / 100 = $0.1 (per user).

Trial started – calculate an average revenue only among those new users, who have started a trial.

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Note

For example, we have 100 new users created within the selected period. And 50 of them have started a trial. These users have paid $10 by now. ARPU is equal to $10 / 50 = $0.2 (per trial user).

Cohort period

Default value - Max. Number of the days (0-365) or Max (no limitation). Day 0 is the 24 hours from the moment when user is created. Day 1 is the next 24 hours and so on.

This setting might be used to understand the average revenue to the Nth day of user life. So you can estimate the moment when the paid installs are paying off.

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Note

For example, if ARPU for new users by the Day 3 is $0.1, this means that an average user brings $0.1 to the 4th day of his/her lifetime.

Why ARPU is important?

One of the main goals of any mobile business is to maximize revenue. ARPU is one of two critical values for calculating your ROI along with CPI (cost per install).

Knowing the ARPU of different groups of users will let you optimize your marketing efforts and focus on high-performing user acquisition campaigns. ARPU-driven measurement help to point out which media sources could bring the top paying users and which are under-performing and should be stopped.

Understanding who is your high LTV users can help to find more like them through lookalike campaigns and leads you to boost total app revenue.

ARPPU

Cohorts: Yes.

ARPPU is Average Revenue Per Paying User.

It's pretty much the same as ARPU, except there are only paying users counted within the selected time period.

You can choose whether to calculate ARPPU using Sales or Proceeds.

Calculate users by events

Purchase – count all new paying users in the selected cohort for ARPPU calculation.

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Note

For example, we have 100 new paying users created within the selected period. These users have paid $200 by now. ARPU is equal to $200 / 100 = $2 (per user).

Trial converted – calculate an average revenue only among those new paying users, who have converted from a trial.

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Note

For example, we have 100 new paying users, created within some selected period. And 50 of them have converted from a trial. These users have paid $200 by now. ARPPU is equal to $200 / 50 = $4 (per free trial user converted into customer).

Cohort period

Default value - Max. Count of the days (0-365) or Max (no limitation). Day 0 is the 24 hours from the user’s creation. Day 1 is the next 24 hours and so on.

This setting might be used to understand the average revenue to the Nth day of the paying user life. So you can estimate the moment when the paid installs are paying off.

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Note

For example, if ARPPU for new paying users by the Day 3 is $1, this means that an average paying user brings $1 to the 4th day of his/her lifetime.

Additional notes

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Important Note

Both ARPU/ARPPU are calculated without refunds. Downgrades (partial refunds) difference is counted.

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Note

ARPPU will be usually much higher than ARPU because only paying users included in cohorts (a smaller part of all users in the app).

ARPAS

ARPAS is the Average Revenue Per Activated Subscription.

It’s calculated as the average revenue per paying users or free trial subscribers (inclusing those who started a free trial within the selected time period).

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Imprortant

Revenue from non-subscription purchases are also included in the ARPAS metric calculation.

Cohorts: Yes.

You can choose whether to calculate ARPAS using Sales or Proceeds.

Cumulative LTV

Cohorts: Yes.

The Cumulative LTV chart shows a cumulative (accumulative) revenue. You can check LTV using the following calculation options for selected cohorts up to 999 days:

  • ARPPU (average revenue per paying user)
  • ARPU (average revenue per user)
  • ARPAS (average revenue per activated aubscription)

This is a cumulative dynamic of how the average revenue from a selected group of paying users grows within the selected cohort period (i.e. days after installation).

Cumulative СLV

Cohorts: Yes.

The Cumulative СLV (Customer Lifetime Value) chart shows a cumulative (accumulative) revenue. The CLV calculation is based on cohorts from the first paid transaction (but not from installaion) and on the ARPPU metric.

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Note

When segmented by Product it counts all renewals taking into account the number of users that were in the cohort when the first paid transaction occurred.

If a user changed the subscription within the selected cohort period (e.g. on Day 20) it still counts the original number of users in Product1 and it will increase the number of users in Product2 starting from Day 20.

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Note

When segmented by First product it counts all renewals to the original product nevertheless users changed subscriptions or not.

Cohort Proceeds


This is a cohort chart illustrating the proceeds revenue generated by users who installed the app within the specified dates.
For example, if the chart indicates $2,500 for June 4, it means that users who installed the app on that date collectively generated $2,500 in proceeds revenue.

As time progresses, the revenue for each cohort will typically increase, reflecting the ongoing revenue contributions from users who continue to engage with the app.

CHURN

Subscriptions churn

Cohorts: No.

This metric shows how many subscriptions were lost during the selected period.

Subscriptions Churn = (Number of subscriptions expired during the period) / (Number of paid subscriptions at the start of the period) * 100%

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Important Note

Number of paid subscriptions at the start of the period means that any new subscriptions, that could happen inside the period are not included.

Churn also can be negative. This may happen if your app allows customers to have more than one subscription at the same time and the user adds a purchase to existing ones. It's called "expansion". Negative churn is a signal that your app has a strong value to your customers.

Churned revenue

Cohorts: No.

This metric shows how much revenue was lost during the selected period.

Churned revenue = (MRR Lost to Downgrades + MRR expirations in the period) / (MRR at the start of period) * 100%

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Important Note

MRR at the start of the period means that any new MRR inside the period is not included.

Churned revenue especially helpful to ensure that you're not losing the most valuable customers (subscriptions churn can be relatively low while churned revenue is high).

Like subscriptions churn, revenue churn also can be negative if users upgrade subscriptions or subscribe more within your app. And, of course, it's a good signal too.

USERS

New users

Cohorts: No.

Yes, these are just new users of the app calculated by First Seen Date. By the way, you can filter them, using custom User Properties (if you send any).

More information about how Apphud tracks new installs available here .

Read more about First Seen Date here.

CONVERSIONS

All charts in this group represented as funnels with particular steps (based on events).

New users are calculated as cohorts. It means that users are "grouped" by the initial event date (i.e. users, who have installed the app on a particular date).

For example, if we have a row with a date of Jan, 28, then trial conversions are summarised by users who had installed the app on Jan, 28 and then converted to regular subscribers any day after install and trial start (not only on Jan, 28).

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Note

Note that all conversion events are grouped by new users.

So, if your app allows two simultaneous subscriptions (say, with a trial period), then it will be counted as the single user who started a trial (not two trials).

The same works for trial conversion events – if there are two trials that were converted to regular subscriptions by the user within the app, we'll show this as a single user who converted from the trial(s) to subscriber.

Active subscriptions

Active Subscriptions chart shown as the number of the regular (unexpired) paid in-app subscriptions at the end of each selected period.

Cohorts: No.

You can segment by the renewal type to learn the trend of the renewal enabled / disabled subscriptions.

Trial conversion

Cohorts: Yes.

New users, who started a trial and then converted to regular subscribers. Users who converted without a trial period are not counted.

Regular subs. conversion

Cohorts: Yes.

New users, who converted to regular subscribers (trial conversions are not included).

Paid intro conversion

Cohorts: Yes.

New users, who started a paid intro offer and then converted to regular subscribers.

Promo offer conversion

Cohorts: Yes.

New users, who started a promo offer and then converted to regular subscribers.

Non-renewing purchase conversion

Cohorts: Yes.

New users, who purchased a non-renewing in-app product.

Segments

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Note

You can segment conversion charts by the second additional parameter to get more meaningful results.

View parameters

For example, you have 100 new users, 10 of them started a trial and 2 were converted to a subscription.

% of total

Shows drop-off in each funnel step calculated as a percent of total (first step) count.

In this case, the total count (new users) will be 100%, the trial started – 10%, and converted – 2%.

% of previous

Shows drop-off in each funnel step calculated as a percent of the previous step.

New users will be 100%, the trial started – 10% and converted – 20% (because started trials are considered as 100% in this case).

User count

Shows absolute users count in each step.

Exclude refunds

Default: disabled.

Note that, we calculate all values including transactions with refunds by default. If you want to analyze only "successful" conversions, turn on Exclude refunds option.

Keep in mind, that you can see lower conversions in this case.

EVENTS

Trial subscriptions

Cohorts: No.

Analyze events related to trials:

  • Trial started
  • Trial expired
  • Trial converted
  • Trial cancelled

Regular subscriptions events

Cohorts: No.

Analyze regular subscriptions:

  • Subscription started
  • Subscription renewed
  • Subscription cancelled
  • Subscription expired
  • Subscription refunded

Paid intro offers

Cohorts: No.

Analyze paid intro subscriptions:

  • Intro started
  • Intro renewed
  • Intro converted
  • Intro expired
  • Intro refunded

Promo offers

Cohorts: No.

Analyze promo offer subscriptions:

  • Promo started
  • Promo renewed
  • Promo converted
  • Promo expired
  • Promo refunded

Non renewing purchases

Cohorts: No.

Analyze Non renewing purchase events:

  • Non renewing purchase
  • Non renewing purchase refunded

Paywall events

Cohorts: No.

Analyze paywall events:

  • Paywall shown
  • Paywall closed
  • Paywall checkout initiated
  • Paywall payment canceled

Other events

Cohorts: No.

Analyze other events:

  • Autorenew enabled
  • Billing issue