Reports in this section are designed specially for games projects and allow to analyze games economics. You can find here information about in-game purchases, levels, locations, in-game currencies balances distributed by levels, etc
In-Game Analysis reports:
This dashboard presents an overview of data related to in-app purchases. All data is shown for a specified period of time (last 30 days are selected by default).
The first widget shows the dynamics of main in-game currencies for the first 20 levels.
Widgets “Top purchases” and “Top 3 purchases by days” show top in-app virtual purchases. “Top purchases” show purchases ordered descending by the amount of bought items. “Top 3 purchases by days” widget shows daily dynamics of top 3 items.
Widget “Top levels by revenue” shows levels stats:
Gross on each level
Number of users that completed a particular level
Number and % of users remaining on a level
Number of paying users and paying share
Click a to open a more detailed report.
The Economy Balance report shows the amount of in-game currency earned, bought, spent and kept in the account on each level. The data is aggregated when a level is completed.
There are two pages available:
Currency balance by level shows how much virtual currency is bought, earned, spent and kept in accounts on each level (chart or table mode)
Earned / bought currency shows the ratio of earned and bought amount of virtual currencies in percentage values
You can choose the way the data is aggregated in the report: total sum or average number.
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. Press “Refresh” button to apply the changes.
The Virtual Goods & Purchases report shows the detailed overview of how users spend in-game currency.
There are 4 pages available:
Structure of purchases
Dynamics of purchases
To build the report, click the "View result” button. If you would like to build the report after changing settings, use the “Refresh” button.
It is possible to set the range of levels you are most interested in for each page.
Moreover, you can configure a filter in the reports, use already created filter template or custom segment to get more detailed data.
The Top purchases page shows top 5 in-game items based on the number of purchases that can be grouped by levels or days. You can check this statistics for all in-game currencies. The default period for this report is 5 weeks.
The Purchases structure page is represented by a table that shows item-by-item statistics for a chosen in-game currency:
The number of purchases
How much in-game currency spent and the share of these spendings among total spendings for this particular currency
Average price of this item among all levels/dates
The minimum level on which this item is purchased
The default period for this report is last 30 days.
The Purchases dynamics report allows you to check fluctuations of user spendings for a set of particular items (up to 5) that can be selected/deleted/added manually. Data can be aggregated in two ways: as a sum or averaged number. The report can be presented as a line or bar chart. You can group the report by levels or by date.
The default period for this report is last 30 days.
ABC/XYZ-analysis divides the set of items purchased for a chosen currency into 9 segments based on the amount of revenue that is generated by a particular item and stability of demand.
Those categories are:
High contribution to the revenue structure - Goods that make up 80% of all purchases
Average contribution to the revenue structure - Goods in 80%, but out of 90% of all purchases
Low contribution to the revenue structure - Goods out of 90% of all purchases
Stable demand - Demand fluctuations up to 60%
Moderately stable demand - Demand fluctuations from 20% to 60%
Unstable demand - Demand fluctuations more than 60%
The default period for this report is the last 30 days.
This report shows the distribution of users among players’ levels (of experience), locations and cumulative metrics.
There are three pages available:
Cumulative metrics by level
On each page you can choose up to 3 metrics to track and select a time period. On the “Player levels” page the last activity date is used, on the “Locations” page - calendar date, on the “Cumulative metrics by level” page - install date.
To build the report, click the “View result” button. If you would like to build the report after changing settings, use the “Refresh” button. Moreover, you can configure a filter in the reports, use already created filter template or custom segment to get more detailed data.
On the Player levels page you can track user related metrics grouped by levels (of players’ experience):
The number of users that completed or remain on a particular level in absolute and percentage values
The amount of generated revenue
Cumulative metrics by level - this report shows cumulative metrics in the context of game levels (player experience), using the report you can predict what income and at what level the user will bring.
The report contains the following metrics:
Cumulative ARPU by level - cumulative income of the average user at each level
Level ARPU - average income from one active user at each level
Level conversion - conversion to the first payment by level, the number of users who made a payment on a certain level divided by the number of applications installed.
Cumulative level conversion - cumulative conversion to the first payment by level
Users reached the level - the number of users at the game level
You can evaluate how much a player will bring to a project to a particular level, compare the value of game levels, determine which levels are most profitable, evaluate the change in accumulative metrics after processing a game level.
Cumulative ARPU by level allows you to compare cohorts, for example, when you made any changes to the product. To find out if users began to pay more or less you can compare the dynamics of cumulative ARPU for cohorts that installed the application before or after changes.
Cumulative conversion by level will also help to analyze the changes in the product. For example, earlier, 1% of users was converted to a purchase at the 20th level, but after a new release 1.5% of users began to be converted. You can’t notice such changes on the regular conversion chart by level, because it could be redistributed: before users paid more at the 3rd and 8th levels, now - at the 5th and 6th levels. Thanks to the levels at which the changes were made, cumulative conversion will let you know if more users were converted to the purchase than before the changes.
It will also be useful to compare the behavior of cumulative conversion and cumulative ARPU by level. For example, cumulative conversion has increased, and cumulative ARPU to the 20th level has become lower than before the changes, this may indicate that there are more paying users but they pay less.
It is important to note that for the payment event at the level we take exactly the level at which the payment was made (not the one at which the player is currently located).
The Locations report shows statistics about quests, game levels, etc. Therefore, here you can find both user related and location related metrics:
Location complexity (the rate of successful attempts)
The number of successful/unsuccessful attempts needed to pass the location
The amount of users’ earnings and spendings for real and virtual currencies
There are two types of metrics aggregation – total sum and average.