Streaming Data Analytics Platform for TMEG

Mactores’ Streaming Data Analytics Platform for TMEG delivers real-time insights into platform health, user experience, and content performance across OTT, gaming, and interactive media ecosystems. Designed for companies that must monitor billions of streaming events per day, the solution empowers teams to take immediate, data-driven actions that improve customer satisfaction and reduce churn.

Business Needs

Streaming providers face several challenges, including unpredictable spikes in demand, varied device behavior, and the complexity of delivering high-quality content over heterogeneous networks. Traditional batch-based analytics fail to meet the immediacy required to maintain viewer engagement and operational performance. This platform solves that problem by enabling low-latency analysis of telemetry data to optimize user experience, infrastructure performance, and content monetization.

Mactores Solution

Macores’ Streaming Data Analytics Platform for TMEG solution captures real-time telemetry across streaming channels, including mobile apps, smart TVs, gaming consoles, and browsers using Amazon Kinesis Data Streams and Kinesis Video Streams.

Data points such as buffering events, playback quality, error codes, CDN behavior, session start/drop, and user interactions are processed in milliseconds.

Using Amazon Kinesis Data Analytics, the platform performs stream enrichment, aggregations, and anomaly detection in real time. Alerts for failures, regional drops, or degradation in quality are triggered via AWS Lambda. Amazon SageMaker enables ML-driven churn prediction and content personalization models that are integrated directly into the processing pipeline.

Processed telemetry is stored in Amazon S3 and Amazon Redshift. AWS Glue organizes this data into refined datasets, enabling retrospective analytics, experimentation (e.g., A/B testing), and insight generation through Amazon QuickSight dashboards.

The platform provides a 360-degree operational view across delivery channels to proactively resolve issues and boost customer retention.

AWS Services Used

Amazon Kinesis Data Streams: Capture real-time telemetry (buffering, bitrate, device usage, etc.).

Amazon Kinesis Video Streams: Process real-time video stream metadata for diagnostics.

Amazon Kinesis Data Analytics: Analyze streaming data on the fly, detect anomalies.

AWS Lambda: Automatically respond to streaming issues or performance drops.

Amazon SageMaker: Predict viewer churn and personalize content using ML.

Amazon DynamoDB: Store low-latency metadata about active sessions and devices.

Amazon S3: Store raw and processed telemetry data at scale.

Amazon Redshift: Enable scalable historical analytics and report generation.

AWS Glue: ETL and data transformation to prepare telemetry for analysis.

Amazon QuickSight: Create operational and business dashboards with streaming metrics.

Amazon CloudWatch: Monitor infrastructure health and trigger alerts.

Benefits

Real-Time Monitoring: Immediate detection of anomalies in streaming performance, across user devices and geographies

Enhanced Viewer Retention: Personalized content and proactive issue mitigation powered by machine learning

Unified Telemetry Architecture: Centralized pipeline across media types and channels

Faster RCA & Remediation: Real-time alerts, metrics, and ML models reduce mean-time-to-detect and resolve incidents

Data Democratization: Role-based dashboards enable engineering, operations, and business teams to access relevant insights

Business Impact

Customers leveraging this solution report over 40% improvement in incident response time, reduction in video abandonment rates by up to 30%, and higher engagement metrics through intelligent content delivery. It also helps reduce churn by identifying quality degradation patterns early and providing actionable intelligence to customer experience and engineering teams.