Retention analytics is used in gaming platforms to analyze player retention and evaluate the effectiveness of marketing strategies. The analytics system allows you to track user activity and identify the reasons for the decline in engagement.
Retention analysis helps determine which players remain active, which are beginning to lose interest in the platform, and which factors influence their behavior. This allows the platform to launch timely marketing activities to retain users.
Back-office system collects data on player behavior, deposits, game activity and bonus usage. This data is analyzed to determine the level of user retention and the effectiveness of various retention tools.
JackCode implements retention analytics systems for gaming platforms, allowing you to analyze player behavior, optimize marketing campaigns and increase long-term user activity.
The main tasks of retention analytics:
- Player Retention Analysis
- Identifying the causes of user churn
- Evaluating the effectiveness of marketing campaigns
- Player activity monitoring
- Optimization of retention strategy
- Custom Segment Analysis
- Improve player lifecycle
What metrics are used in retention analytics
| Metrics |
Appointment |
| Retention Rate |
Player Retention Percentage |
| Churn Rate |
User churn rate |
| Session Frequency |
Frequency of gaming sessions |
| Player Lifetime Value |
Player life value |
| Deposit Activity |
Deposit activity |
| Engagement Score |
User Engagement Level |
What data is analyzed by the system
| Data type |
Appointment |
| Player Activity |
User activity |
| Game Sessions |
Gaming sessions |
| Transaction Data |
Financial transactions |
| Bonus Usage |
Use of bonuses |
| Communication History |
Communication history |
| Marketing Campaigns |
Marketing campaigns |
What retention analytics controls
| Component |
Appointment |
| Retention Dashboard |
Hold Analysis Dashboard |
| User Segmentation |
User segmentation |
| Behavior Analytics |
Player behavior analysis |
| Campaign Tracking |
Tracking marketing campaigns |
| Player Lifecycle Analysis |
Life Cycle Analysis |
| Performance Metrics |
Performance metrics |
Typical Retention Analysis Process
| Stage |
Description |
| Data collection |
The platform collects player data |
| Behavior analysis |
The system analyzes user activity |
| Define Segments |
Players are allocated to segments |
| Problem identification |
Causes of outflow are determined |
| Marketing launch |
Activated retention campaigns |
| Analysis of results |
Effectiveness of actions is evaluated |
Benefits of retention analytics
| Advantage |
Practical value |
| Deep player analytics |
Understanding user behavior |
| Reducing audience churn |
Players stay on the platform longer |
| Marketing optimization |
Marketing works more accurately |
| Increase player LTV |
Increasing user value |
| Improving the user experience |
Platform adapts better to players |
Who uses retention analytics
| Participant |
Role |
| Analytics Teams |
Analyze player behavior |
| CRM Teams |
Manage custom segments |
| Marketing Teams |
Optimize marketing campaigns |
| Operations Teams |
Monitor platform activity |
| Product Managers |
Develop retention strategies |
Retention analytics allows the gaming platform to analyze user behavior, optimize marketing strategies and increase long-term player activity.
