The missing element in game analytics
Cheat detection and management
Because precise identification of unfair play should be an industry best practice
In the fast-paced world of mobile gaming, dealing with cheaters and fraudulent activity is a resourceful headache. It abuses IAP revenues, mess-up game analytics metrics, lead to unhappy, frustrated players and more
insights based on in-game device sensor-based data signals in real-time serve to detect:
- Commercial cheating
- Modded APKs and IPAs
- Wall hacks
- Speed hacks
- Account sharing
- IAP abuse
Retention & monetization optimization
Engage players and cross promote your game brands by identifying players sentiment
Maximizing monetization while keeping players engaged and without cannibalizing existing achievements is a delicate balancing act.
Effectively categorizing new players, within the first 24 hours can help tailor the best approach to play segmentation, retention and cross promotion.
Identifying frustration and churn probability among engaged players completes the picture and fills today’s accuracy gaps of the industry
Leverage Quago’s predictions and insights to:
- Prevent churn and re-engage players
- Cross-promote other games ONLY to relevant players
- Advertise to non-paying users without risking IAP revenue
- Segment players by churn probability, pLTV, skill level and more
- Matchmake new players accurately
UA optimization and CPA fraud detection
Ensure every dollar spent delivers a return
In the realm of user acquisition (UA), success is not measured by installs but by the eventual ROI and ROAS attributed to channels and campaigns.
While attribution tools protect against install-based fraud, CPA fraud isn’t properly solved.
Quago detects post-install CPA fraud accurately, within the first 24 hours, without compromising user privacy, allowing game publishers to optimize campaigns and get reimbursed for fraudulent ones.
WIth Quago you can:
- Quickly identify in-game CPA fraud (post install)
- Provide clear evidence of fraud to be reimbursed by ad channels
- Optimize UA campaigns based on pLTV score as soon as 24 hours from initiation
Make smarter decisions Eliminate in-game blind spots
- pLTV scoring
- Churn prediction
- Engagement levels
ML based technology: a new level of data and insights
Machine learning is leveraged to make sense of billions of sensor-based, physical signals that represent player interactions with their device while playing
Quago hunts for patterns, looking at data coming from the device touch metrics, accelerometer, gyroscope, device tilt, and more – to understand player behaviour and motivation, in a way that no other game analytics platform can.
The system is trained on over 100 Million DAU and knows how to generate insights based on historical data coming from millions of players
A must-have add-on SDK to any game
- Patent pending technology
- Light SDK – ~1 MB
- Negligible CPU consumption (~0.1%)
- No impact on performance and stability
- No need to increase cloud resources
- Privacy compliant – no collection of PII