User Cohort Analytics groups users by their unique properties, and uses the groupings to study the differences between each user groups’ main indices and their game play patterns in accordance with the time.
Classify users into cohort groups for more focused and narrowed analysis between customized groups of users. For instance, as a publisher you can assign Non-Paying users with no in-app purchase experience and VIP users with over $100 monthly in-app purchases as user cohort groups to assess the differences in each of these two groups’ DAU, number of sessions, average session time of the users, and other major indices.
Tapjoy provides default cohorts and custom user cohorts. Default cohorts are the basic set of cohorts that are provided after users SDK integration with Tapjoy. Custom user cohorts are the ones publishers can customize freely to their needs.
Basic user cohorts generally used in data analysis. Default Cohorts are provided as soon as you complete your SDK integration with Tapjoy. There are 7 default user cohorts: OS, Country, Referrer, Store, App Version, Device Type, and Paying/Non-Paying
Default Cohort variables under the same category can be used in combination with each other. For example, if you have your country cohort selected as “USA", and you would like to select multiples of game version cohorts at the same time, you can simply select in all game versions you wanted to analyze. Select game version three game version cohorts “1.0”, “1.5”, “2.0”, then you will be able to only index users from USA using the game versions from 1.0 to 2.0. There are limitations on this however; you may only choose up to 5 default cohorts from the 7 variables at a time to compare.
Tapjoy also provides customizable user cohort variables.
Similar to default cohorts, there are limits on the number of cohorts you can use at once for analysis. For custom cohorts however, the number of cohorts you may use simultaneously is 3.
Below are some examples of Custom User Cohort Variables that are generally useful in typical app. You can select up to five of these to apply in your analysis.
In the chart below, cohorts that are labelled with (built in) in their name are the basic cohorts provided by Tapjoy; built in cohorts will not be counted in the user cohort variable limit. Publishers can use 7 basic cohorts (Built In) and additional 5 User Cohort variables in your analysis.
Cohort Type | Cohort Name | Explanation | Usage and Analysis Hypothesis |
Custom User Cohort | User Level Group (Built In) | Distinct user levels into various groups for analysis. (ex, Low Level (1~10),
Middle Level (11~20), High Level (21~30)) | - Creation and modification of Level groups can be done in the “Game/App” menu.
- In order to use the level group cohort, you must integrate Level Data when performing SDK integration.
(As Level Data is sent to the Tapjoy server, Level Group cohort settings screen will automatically appear on the dashboard.) |
Character | Play pattern analysis and core indexes for each character type. | - Used for assessing BM’s applicability, and also used as the basis to identify improvements. | |
Total Play Time | Core indexes and play pattern analysis by differing playtimes. | - Client has the cumulative play time data of the users calculated, if not, the client needs to access DB to acquire cumulative play time data. | |
Purchase | Distinguish users based on their in app purchase amount. | - Cumulative purchases since installment | |
Character/Skin Purchase status | Indices and play patter analysis of the users who purchased characters and skins (Major BM) | ||
Play Ranking | Analyze the effects of in-game ranking on the users’ play patterns or purchase patterns. | ||
Friends Count (Built In) | Analysis by Number of Friends saved or number of team-play participants. | Friends count is provided by SDK in a form of pre-defined. | |
Default Cohort (Built In) | Country | Trace Client Device’s IP in order to analyze player’s location (Country) at the playing moment. | |
Referrer | Analyze marketing activities such as advertisement, Cross promotion, etc. | ||
Store (Android Only) | Analysis of what marketplace the App came from. | ||
App Version | Analyze the effects from the updates of each game versions. | ||
Device Type | Analyze play patterns of the users by each device type | ||
OS | Per OS analysis, in case of managing multiple OS grouped in as a single app. | ||
Paying/Non-paying | Analysis of IAP behavior |
Cohort Type | Cohort Name | Explanation | Usage and Analysis Hypothesis |
Custom User Cohort | User Level Group (Built in) | Use( )/Not Use( ) | Segment user levels into several group for analysis. (ex, Low Level (1~10), Middle Level (11~20), High Level (21~30)) |
Custom User Cohort (1) | Use( )/Not Use( ) | ||
Custom User Cohort (2) | Use( )/Not Use( ) | ||
Custom User Cohort (3) | Use( )/Not Use( ) | ||
Custom User Cohort (4) | Use( )/Not Use( ) | ||
Custom User Cohort (5) | Use( )/Not Use( ) | ||
Default Cohort (Built In) | Country | Trace Client Device’s IP in order to analyze player’s location (Country) at the playing moment. | |
Referrer | Analyze marketing activities such as advertisement, Cross promotion, etc. | ||
Store (Android Only) | Analysis of what marketplace the App came from. | ||
App Version | Analyze the effects from the updates of each game versions. | ||
Device Type | Analyze play patterns of the users by each device type | ||
OS | Per OS analysis, in case of managing multiple OS grouped in as a single app. | ||
Paying/Non-paying | Analysis of IAP behavior |