Digital Service Optimization Based on Customer Behavior - Leading Financial Insurance Company K
K Insurance, which lacked a web service log collection infrastructure, built a flexible integration architecture with an asynchronous messaging framework and streamed user behavior logs in real time to internal systems and external solutions. This improved the speed of identifying needs and service improvements based on user traffic analysis, greatly enhancing digital service quality.
Challenge
K Insurance, accelerating digital transformation, needed to improve services using customer behavior logs, but existing integration systems had limitations in real-time data processing. The architecture for handling large log volumes was insufficient, delaying service optimization based on user behavior, and complex integration between systems reduced scalability and operational efficiency.
Solution
Introduced a Kafka-based high-performance messaging platform to resolve data processing bottlenecks between integration systems and implemented asynchronous data flows. Collected UI logs in real time to Kafka topics and used Confluent Sink connectors to automatically link to the analytics platform. Optimized the design for DevOps environments and established integrated monitoring for automated and visible log pipelines.
Results
- Real-time analysis of customer behavior data: Shortened service improvement cycles based on user interactions
- Enhanced system flexibility and scalability: Secured ease of change with a loosely coupled structure
- Automated log processing and improved analysis efficiency: Accelerated insight generation by optimizing the data pipeline
- Provided personalized insurance service experiences: Implemented customized services based on customer behavior patterns