ING achieves 3x gain in marketing response with personalization
Company Size
1,000+
Region
- Europe
Country
- Netherlands
Product
- IBM Campaign
- IBM Digital Analytics for On Premises
- IBM PredictiveInsight
- IBM Marketing Operations
- IBM Interact
- IBM Contact Optimization
- IBM Netezza TwinFin 24
Tech Stack
- IBM EMM technology
- IBM Digital Analytics
- IBM Netezza TwinFin 24
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Revenue Growth
Technology Category
- Analytics & Modeling - Real Time Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
- Functional Applications - Enterprise Resource Planning Systems (ERP)
Applicable Industries
- Finance & Insurance
Applicable Functions
- Sales & Marketing
Use Cases
- Demand Planning & Forecasting
- Predictive Maintenance
- Supply Chain Visibility
Services
- Data Science Services
- System Integration
About The Customer
ING Bank is a Dutch multinational banking and financial services corporation headquartered in Amsterdam. Its primary businesses are retail banking, direct banking, commercial banking, investment banking, wholesale banking, private banking, asset management, and insurance services. With total assets of US$1.1 trillion, it is one of the biggest banks in the world. It constantly looks for ways to improve its services and customer experience.
The Challenge
ING Bank was facing challenges with its marketing campaigns which were slow, costly and losing effectiveness. The bank had no single customer view and cycle times for campaigns could exceed 20 weeks. Inbound channels could not be supported with the previous solutions. A lack of relevance and coordination across channels generated subpar results while driving up costs. The bank recognized the need to rebuild its marketing technology infrastructure and processes to become more automated, coordinated and personalized, as well as take advantage of inbound marketing opportunities.
The Solution
ING embarked on a customer differentiation program, restructuring its marketing organization into a centralized framework and implementing IBM EMM technology to coordinate and personalize campaigns across multiple channels through the use of next-best action models based on customer history and recent interaction. The bank has deployed the IBM Digital Analytics for On Premises solution to recognize customers and integrated the solution with its IBM EMM-based next-best action engine. By combining extensive offline customer profile data with customer activity on its website, ING is able to present more personalized NBA offers. Web activity data is used to rerank NBA offers to deliver messages that are top of mind for customers, improving marketing effectiveness.
Operational Impact
Quantitative Benefit
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