Industry
Client Overview
A mid-market mobile game publisher with a successful puzzle RPG. While the game had a solid player base, it struggled with long-term retention. Players would either get stuck on a difficult level and quit in frustration, or find the game too easy and leave out of boredom.
Client Testimonial
"CISIN revolutionized how we look at player engagement. Their AI personalization engine is like having a dedicated game designer for every single player. The impact on our retention and monetization KPIs was immediate and substantial. We are now deploying their system across our entire portfolio." - Product Manager, Gemstone Studios
Problem
A one-size-fits-all difficulty curve was failing to engage a diverse player base. The publisher needed a way to automatically tailor the gameplay experience to each individual's skill level and play style.
Key Challenges
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01
High Player Churn: Significant drop-offs at specific difficulty spikes.
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02
Poor Monetization: Free-to-play users weren't converting because they never felt the "need" for a power-up, while paying users would burn through content too quickly.
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03
Lack of Data Insights: They were collecting data, but didn't know how to use it to dynamically influence gameplay.
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04
Manual Balancing is Ineffective: Manually tuning hundreds of levels for millions of players was an impossible task.
Our Solution
We implemented our "Player-Experience Modeling" service, delivered by a dedicated "Data Visualisation & Business-Intelligence Pod."
Data Pipeline & Ingestion: We first built a robust pipeline to collect and process gameplay telemetry from all players in real time.
Player Skill Modeling: We used a machine learning model to analyze gameplay data (e.g., moves per second, level completion time, hint usage) to assign a dynamic "skill rating" to each player.
Dynamic Difficulty Adjustment (DDA): We created an AI system that adjusted key level variables (e.g., number of moves, types of obstacles, enemy HP) in real-time based on the player's current skill rating. If a player was struggling, the game would subtly get easier; if they were cruising, it would present more of a challenge.
Personalized Offer Engine: We linked the DDA system to the in-game shop. A player struggling on a level might be presented with a timely, discounted offer for a relevant power-up, increasing the likelihood of conversion.
Implementation & Execution
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Data Audit (Week 1)
We analyzed their existing analytics setup and defined the key events we needed to track.
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Pipeline Build (Weeks 2-4)
Our data engineers built the AWS-based data pipeline to handle millions of events per day.
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Model Training (Weeks 5-8)
Our data scientists trained the initial player skill model using historical player data.
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A/B Test Integration (Weeks 9-10)
We integrated the DDA system into the game behind an A/B test flag, allowing us to roll it out to a small percentage of players.
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Live A/B Test (Weeks 11-14)
We ran a month-long A/B test comparing the DDA group against the control group.
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Full Rollout & Dashboarding
After the test showed overwhelmingly positive results, we rolled the system out to 100% of players and provided the client with a live dashboard to monitor its impact.
Positive Outcome
The implementation of the adaptive AI system delivered immediate and substantial results, solidifying the client's market position and protecting their bottom line.
1. 18% Reduction in Fraud Losses
22% Increase in Day-30 Retention: The personalized experience kept players engaged for longer, dramatically improving the game's core retention metric.
2. 12% Increase in Average Revenue Per Daily Active User (ARPDAU)
The personalized offers were more effective, leading to a significant uplift in revenue.
3. Reduced Churn at Key Blockers:
Churn rates at previously identified "problem levels" dropped by over 50%.
4. Data-Driven Design
The client's design team could now use the skill rating data to inform the creation of new levels and features.
Why Choose Us
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Deep AI Specialization
Our expertise in machine learning and player modeling was key.
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Flexible Engagement PODs
The dedicated BI Pod had the exact skills they needed.
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World-Class In-House Talent
A team of data scientists and engineers delivered the solution.
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Proven Track Record
Our experience with mobile analytics gave them confidence.
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Accelerated Time-to-Market
e delivered a production-ready system in under four months.
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Full IP & Data Ownership
They owned their player data and the models we built.
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Risk-Free Trial
The A/B test approach was a low-risk way to prove value.
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Global Delivery, Local Support
We provided constant updates and analysis.
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ROI-Focused Approach
We tied every technical decision back to its business KPIs.
Conclusion
CISIN provided a sophisticated, data-driven AI solution that fundamentally changed the client's approach to game design and live-ops. By personalizing the player journey, we created a more engaging product and a more profitable business.