Pricewise Case Study: Deep Dive into Implementation
How a leading Dutch price comparison platform consolidated 4 product databases into unified analytics, achieving €2.6M in annual value through data-driven insights.
Company Overview: Pricewise
Pricewise is a leading Dutch price comparison platform helping consumers find the best deals on essential services including energy, insurance, mortgages, and telecom products.
- Industry: Price Comparison / Affiliate Marketing
- Business Model: Online platform for comparing essential service prices
- Challenge: Legacy on-premises data warehouse unable to scale
- Solution: Mara Data Warehouse (Nexus Model Architecture implementation)
The Challenge: Legacy Infrastructure Bottleneck
Pricewise operated a successful platform but their data infrastructure had become a critical bottleneck:
Technical Challenges
- Legacy Architecture: On-premises SQL Server (SQL1) with manual ETL processes
- Data Silos: Separate databases for each product line (Energy, Insurance, Telecom, Mortgages)
- Manual Reporting: Weekly manual data extraction and consolidation
- Limited Analytics: No self-service BI; all reports custom-built by IT
- Long Development Cycles: 6-8 weeks to integrate a new data source
Business Impact
- Slow Decision-Making: Delayed reporting due to manual processes
- Missed Opportunities: Lack of real-time insights
- High Maintenance Costs: Custom scripts for every source
- Scalability Issues: Unable to support business growth
- Compliance Concerns: Manual data handling risks
The Solution: Mara Data Warehouse
Pricewise implemented the Nexus Model Architecture as their "Mara" data warehouse—a comprehensive solution spanning the full data lifecycle.
Key Features Implemented
1. Metadata-Driven ETL
20+ source systems mapped with reusable SSIS packages and no custom code per source.
2. Timeslice-Based History
All dimensions track historical changes automatically with ValidFromDate/ValidToDate.
3. Fallout System
Average fallout rate 2-3%, enabling graceful error handling without blocking pipelines.
4. EAV for Product Flexibility
Product-specific attributes handled without schema changes.
5. ResultLog Customer Journey Tracking
Complete funnel analysis from search to conversion.
Business Outcomes: €2.6M Annual Value
Operational Efficiency
- ETL Development Time: Reduced from 6-8 weeks to 3-5 days per source
- Report Generation: Weekly manual reports → Daily automated dashboards
- Data Quality: 97% accuracy with fallout rate monitoring
- IT Maintenance: 60% reduction in support hours
Business Performance
- Revenue Impact: €2M additional annual revenue from marketing insights
- Cost Savings: €600K annual savings in ad spending optimization
- Conversion Rates: 15% improvement after funnel optimization
- Time-to-Market: New product category launch from 3 months to 4 weeks
Scalability Achievements
- Data Volume: Supported 3x growth in data volume over 2 years
- Source Integration: Added 15 new data sources with minimal effort
- Advanced Analytics: Foundation for ML-based product recommendations
Conclusion: From Bottleneck to Strategic Asset
The Mara Data Warehouse implementation demonstrates the transformative power of the Nexus Model Architecture:
What began as a data infrastructure bottleneck became the foundation for Pricewise's data-driven growth, enabling €2.6M in annual value through operational efficiency and strategic insights.
Key Takeaways
- Unified Platform: Consolidated 4 product databases into a single source of truth
- Rapid Integration: New data sources integrated in days, not weeks
- Automated Quality: Built-in monitoring and fallout handling
- Scalable Architecture: Grew from bottleneck to supporting 3x data volume
- Business Impact: Foundation for advanced analytics and ML initiatives
The Nexus Model Architecture transformed Pricewise's data infrastructure from a cost center into a profit center, proving that thoughtful data architecture can drive both operational excellence and strategic advantage.