Banking & Insurance
How to keep your customers: anticipate cancellations with a modern data warehouse
The Challenge
In order to proactively reduce customer churn, a leading insurance company wanted to create precise cancellation forecasts. The existing data warehouse (DWH), which was getting on in years, could no longer meet the increasing demands for speed and flexibility. In addition, outdated technologies led to high operating costs and made it difficult to implement new requirements.
Our solution
To meet these challenges, the DWH was comprehensively modernized. New data sources were integrated automatically and the database objects and ETL processes were redesigned. By using the Oracle Golden Gate replication solution, near-real-time data management was implemented, which made it possible to process current data almost in real time.
The result
The modernization of the DWH led to a significant reduction in operating costs. The introduction of the new ETL technology improved performance and shortened the time-to-market for new requirements. Near-real-time data management enabled the company to predict cancellations based on data and initiate targeted measures to retain customers. In addition, the DWH was adapted to the EU GDPR, ensuring compliance with current data protection guidelines.
The modernization also enabled the integration of new data and the implementation of numerous new features: The use of real-time data enables web clip analysis, while pattern recognition allows typical customer behavior prior to cancellations to be analyzed and countermeasures to be taken at an early stage. The modernized DWH also allows for optimized recommendation management through the central storage and evaluation of relevant customer data. This enables the automated suggestion of individually tailored offers, such as family insurance for recently married customers.
TL;DR: The most important points in a nutshell
Added value through DWH modernization
- Early termination forecasts - identification of customers at risk of churning in order to implement targeted countermeasures at an early stage
- Increased customer loyalty - proactive measures based on current data to reduce customer churn
- Faster decision-making - near-real-time data management for immediately usable insights
- Cost efficiency - reducing operating costs by replacing outdated technologies
- Greater flexibility - faster implementation of new requirements thanks to optimized ETL processes
- GDPR compliance - ensuring compliance with current data protection guidelines
- Advanced customer analysis and targeting - use of web clip analysis, automated pattern recognition and improved recommendation management for individually tailored offers
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