Monetization reports
Reports in this section cover key monetization metrics.
All reports here require Payment event integration. Learn more about Payment event.
Monetization reports:

Monetization Dashboard

This dashboard contains an overview of key monetization metrics. All data is shown for a selected period of time (you can change it in the top right corner), default period is the last 7days.
The top two widgets show the dynamics of Gross & ARPU and Paying share & ARPPU metrics.
Three pie charts below show a Total Gross, Total paying users and Total ARPPU for top 5 countries and the “other” group (includes all countries that didn’t get in the top by certain metric).
The following widgets show more detailed info about repeated payments:
    Repeated payments share in the total revenue
    Users grouped by the number of transactions
    User conversion funnel based on the number of purchases made
    Users grouped by a period within which the first purchase is made
Click a 🔎 to open a more detailed report.

Ad monetization

The report helps you evaluate how users interact with ads in your application.

General Report

The report contains the most common ad performance metrics that we get from Ad networks: ad revenue, ECPM, impressions, average impressions per user, average impressions per session, ad clicks per user.
All data is shown for a selected period (you can change it in the top right corner), the default period is the last 30 days. You can also specify the country or ad network in the filter next to the selection of the report period:
    by adding a country filter, you can measure the effectiveness of ad monetization adjusted for geographic location;
    by adding an ad source filter, you can analyze the effectiveness of a specific ad network.
The report consists of several widgets:
The first widget named Total info for selected period contains general information about metrics that you can use to track several key indicators at once. Metrics are summarized by the ad networks integrated to the project:
    The Ad impressions metric shows how many times ads have been displayed over the selected period.
    Average impressions per user - the average number of ad impressions per user.
    Average impressions per session - the average number of ad impressions per session.
    Ad CTR - the number of clicks on ads divided by the number of their impressions in the application.
    Ad clicks - the number of clicks on ads for the selected period.
    Ad revenue - advertising revenue.
    ARPU by Ad - the average ad revenue per active user for the specified reporting interval. The indicator is calculated by summing the total revenue of the application and dividing it by the number of active users for the specified reporting interval.
You can use this widget to quickly assess the advertising revenue status and other metrics.
The Ad Revenue by network chart depicts ad revenue by ad networks. It shows the percentage of revenue from each ad network:
Ad Revenue by country chart shows ad revenue by country. You can see the percentage of ad revenue in country breakdown:
The Ad metrics per user graph depicts ad revenue, impressions, and clicks per user by days.
The Ad metrics graph displays the following metrics: Ad impressions, Ad revenue, Active users. Thus, you can see the relationship between the number of active users and the advertising income and promptly respond to changes in the number of ad impressions in your application.
Below the charts you can find a table with information about the following metrics:
    Ad revenue.
    Ad click - the total number of times users click or tap on ads shown on your application.
    Ad impressions.
    Ad CTR - the number of times users click on ads shown divided by the number of times ads are shown.
    Ad ECPM - effective cost per thousand impressions. eCPM is an estimate of the revenue you receive for every thousand ad impressions. The higher the eCPM rate is, the better, because it means that the ads shown in the application are doing their job and converting users. You can use this metric to compare ad revenue across ad networks and countries. Therefore, you can select the desired grouping above the table.
Using the Detailed stats chart, you can analyze the following metrics: Ad revenue, Ad clicks, Ad CTR, Ad ECPM, Ad impressions, and ARPU by Ad by weeks. You can also group them by ad network or country.

Advanced report

This section is available only for the accounts linked to the ironSource ad mediation platform. The platform allows you to run an in-depth analysis of your ads and user feedback on it.
To the data in the table, you can apply different groupings as well as double grouping by any of the following parameters: Country, Ad source, Ad unit, Ad Placement, Ad network, etc.
The metrics applicable here are the ones available for the ‘General report’ and others:
    Users saw ad - The total number of unique users who saw an ad over a given time period.
    % of users saw ad - The percentage of users who saw an ad out of all active users. The indicator is calculated by dividing the number of unique users who saw the ad by the number of active users.
    Impressions per user saw ad - The average number of ad impressions per user who saw an ad over the time period. The indicator is calculated by dividing the total number of ad impressions by the number of users who saw the ad.
    Ad revenue per user saw ad - The average ad revenue per user who saw an ad. The indicator is calculated as total ad revenue divided by the number of users who saw the ad.
    Ad impressions per user - The average number of ad impressions per active user over the time period.
If a part of your users fell into the Unknown category, it means that their ad ID was changed and we failed to match them with devtodev users. If you want to convey the trend of a metric over time, you can turn it into a graph that appears below the table.
In Funnels, Custom events, SQL, User flow, New user path, Last user activity (Users), Retention by event reports you can find an auto-created Ad_impression event with the following parameters: Ad network, Ad placement, Ad unit, Ad revenue, Ad Source/ In the user card in ‘Users’ and in the report filters, you can use the following two fields:
    Ad revenue - the ad view revenue generated by a specific user
    Ad impressions - the number of times ads were served to a specific user

Gross Structure

This report presents a set of charts with total stats and day-by-day dynamics for a selected period of time.
Default report period is the last 30 days, you can change it in the top right corner. You can configure a filter in the report or use already created filter template or custom segment to get more detailed data. To apply changes press “Refresh” button.
You can group data in the report with several options:
    Top 5 countries defined by a certain metric, and “other” group (data for all other countries)
    Paying capacity (non-paying / minnows / dolphins / grand dolphins / whales / grand whales)
    Days from app install
    Number of payments
Click a 🔎 to open a more detailed report in Report master.

Conversion to Payments

This report shows info about users' repeated purchases and time they spent in the application before 1st, 2nd, etc purchase.
The top part of the report shows the conversion funnel based on the number of purchases made and detailed info about each step of the funnel in the table: number of users, revenue, median number of payments, median period of time from the first launch until the payment is made.
The last chart shows the number of paying users grouped by two options:
    Days from install until the payment
    Users’ in-game level of experience
It is also possible to check the stats for users with certain number of purchases using a “Payment number” option on the widget. The right part of the last chart contains shares of paying users distributed by predefined groups. When you change widget settings, these numbers also change.
Default report period is the last 30 days, you can change it in the top right corner. You can configure a filter in the report, use already created filter template or custom segment to get more detailed data. Changes are applied automatically.
Top converting goods
This widget contains the information about the top 5 items that users bought as the first purchase. Also, you can expand this report by using the button in the top right corner to see which items were purchased as the second purchase for each of these items.
The report contains the following metrics:
    % of all purchases - a share of purchases for this item among all of the first purchases
    Conversion to 2nd payment after the purchase of the specific item
    Average number of payments by user
    ARPPU - an average revenue that paying users generate for items they purchased, including items that they purchased after they bought specific items as 1st and 2nd purchase
With this widget, you can define the most popular items that your users prefer to buy firstly after they start using your app. Also, you can see the most frequent sequence of purchases and find out which of them more likely lead to repeated payments and more profitable purchases.
For example, you could find out that after users buy item A they are more likely to buy item С and based on this information you could plan your offers strategy and show item С for such users.

Cumulative ARPU

Cumulative N days ARPU is one of the most important metrics of any product. It shows how much money does one average user bring to the project within his/her first N days in the project.
By default devtodev calculates this report for first 30 days of user's lifetime in the project, but you can change the number of days above the chart.
Note that metric “Users, %” shows the calculation user base: how many users (in percentage of the total number of users from the report) were used to calculate the value. For example, if you set the "last 30 days" as install dates interval, and build report for 30 days, there is only one daily cohort which will be used to calculate the ARPU of day 30.
There are two different views in this report:
    Cumulative ARPU. In Cumulative ARPU view you can see the number of installs for each cohort, the total gross each cohort brings within the report time frame.
    The main part of the table shows the cumulative ARPU values for specific days and specific cohorts (cohort is the set of users who installed the project on some specific day(s); every string in the table represents some user cohort). 'Aggregated CARPU' above the table is calculated as weighted average cumulative ARPU (where the weights are the cohort sizes in "Install" column).
    Daily ARPU. In Daily ARPU view you can see how much money does average user from the cohort bring to the project on some specific day. There are two aggregated values above the table:
      'Aggregated CARPU' above the table is calculated as weighted average cumulative ARPU (where the weights are the cohort sizes in "Install" column).
      'Avg. daily ARPU' above the table is calculated as weighted average daily ARPU (where the weights are the cohort sizes in "Install" column).
By analyzing this report vertically you can track the changes of project quality: you compare the same metrics for different time cohorts. By analyzing this report horizontally you can track the payment behavior of each cohort.
You can filter users anyhow by selecting the filter under "Add filter" button.
Aggregated Cumulative ARPU
Cumulative ARPU is one of the key product metrics as it becomes Lifetime Value overtime when it stops changing significantly. Using our new Aggregated CARPU metric in the Cumulative ARPU report, you can track how different cohorts of users spend money, compare those cohorts, and evaluate how different activities influence the metric.
Sometimes, when experiments happen rarely or influence finance metrics only slightly, there is no need to track CARPU every day and compare daily cohorts - that is why we recently added an option to group CARPU by days, weeks or months.
For example, when you select weekly aggregation, the cohorts will be grouped by calendar weeks and CARPU will also be calculated by weeks from the install date. The grouping will be applied to rows and columns of the table. It will allow you to see the dynamics of a bigger cohort of users that might be hardly noticed with daily aggregation.
Please note that the Aggregated cumulative ARPU graph is not cumulative over the entire period and the Cumulative ARPU values on certain days can be lower than the previous day. This is due to the fact that the Aggregated cumulative ARPU is calculated as a weighted mean of all the selected cohort values every day since the installation. The number of cohorts that are part of the calculation will slowly decline because they don’t meet the criteria of having enough days after the installation. Let’s look at an example:
Day 17 CARPU is calculated for all selected cohorts because they were built at least 17 days ago. Day 18 CARPU is calculated only for six cohorts because the seventh (built on July 25th) hasn’t “lived” for 18 days.
The CARPU of the users from the seventh cohort is higher than that of the users from other cohorts. When we eliminate this cohort from the calculation, the weighted mean decreases because its high CARPU increased it.

RFM Analysis

This report shows the distribution of users and revenue based on recency, frequency and size of payments.
There are 5 main segments:
    New paying users
    Rarely paying users
    Inactive paying users
    Inactive new paying users
    Active paying users
Each segment is described in the table widget. You can send a push notification to one of these segments right from the report (use envelop button in the table below the chart).
Default report period is the last 30 days, you can change it in the top right corner. You can configure a filter in the report, use already created filter template or custom segment to get more detailed data. Changes are applied automatically.

Payment amounts

This report shows the distribution of users by the number of payments they made and the total amount of money they paid. For example, in this report you can see how many users registered during a specified time period and made 5 payments with the overall sum of $0 - $5.
Default report period is the last 30 days, you can change it in the top right corner. You can configure a filter in the report, use already created filter template or custom segment to get more detailed data. Changes are applied automatically.

Transactions

This report shows the detailed list of transactions that are made in the app on a particular date. The current date is specified by default.
The following filters are available:
    Source of transaction
    Type of transaction (normal, test, invalid, cheat transactions)
If the list of transactions exceeds 1000, you will be suggested to export a full list as a .csv file. Moreover, you can initiate export manually by clicking the “Export” icon.
Last modified 1mo ago