Impact expansion support
Customer insights
Retention optimization support
Data-driven transformation
The challenge
Unlocking analytics potential for business growth
A financial services and insurance company wanted to enhance its analytics capabilities. For this they needed to do a couple of tasks.
Key challenges
Assessing analytics maturity and business impact
Uncertainty in applying best practices and machine learning
The solution
Powering AI and data to drive business growth
Analytics roadmap
Built tailored roadmaps
Defined strategy based on impact
Established satisfaction and attrition metrics
Data and AI strategy
Applied advanced ML for deep insights
Assessed data readiness via SME insights
Integrated diverse data into a unified platform
Implementation approach
1
Data preparation
Unified diverse data sources
Standardized key metrics
Built a reusable data-mart
2
Advanced analytics
Applied ML techniques
Uncovered hidden patterns
Identified satisfaction and attrition drivers
3
Business impact
Provided actionable insights
Enabled data-driven decisions
Enhanced customer experience
The impact
Driving data-driven transformation
Scalable data solutions
Algorithms power multiple solutions
Helped Enhance data-driven collaboration
Support to strengthen analytics adoption
Customer intelligence
Identified satisfaction drivers
Enabled real-time BI tracking
Optimized retention strategies
Faster decisions
Helped improve insights and actions
Leveraged AI and best practices
Support to improve efficiency over internal teams
Looking ahead
Scaling AI solutions
Expand AI-driven insights across business functions
Continuous optimization
Enhance models with evolving data and feedback loops
Advanced innovation
Leverage cutting-edge ML techniques for deeper impact
