This project provides a data-driven analysis of Shield Insurance, focusing on revenue trends, customer segmentation, and sales mode performance. It helps uncover insights for optimizing sales strategies and customer engagement.
🎯 Problem Statement:
Shield Insurance operates across multiple cities and sales channels. To improve strategic decision-making, the business needs:
- Clear insights into revenue trends, customer behavior, and sales mode efficiency
- Understanding of age-based policy preferences and settlement expectations
- Optimization of engagement strategies based on high-performing segments
This Power BI dashboard provides insights into:
- Revenue Analysis: Monthly trends and city-wise revenue distribution
- Customer Segmentation: Breakdown by age group and sales mode preference
- Sales Mode Performance: Offline vs Online sales channel insights
- Expected Settlements: Age-group wise settlement patterns
- Power BI – Data visualization and dashboarding
- Excel – Initial data transformations
- 💰 Total Revenue:
$989.25Macross all cities - 👥 Total Customers:
26.8Ksegmented by age group and sales channel - 🏙️ Top Performing City: Delhi NCR (
$401.57Mrevenue) - 📈 Most Engaged Age Group:
31-40years (10.4Kcustomers) - 🔍 Highest Revenue Sales Mode: Offline-Agent (
$551M,55.67%share)
| KPI | Description |
|---|---|
| Revenue Growth | Monthly revenue trends across segments |
| Daily Growth | New customer acquisition per day |
| Settlement Value | Expected claim settlement distribution by age group |
| Sales Mode Share | Revenue and customer distribution by channel |
- Identified key growth drivers for targeted engagement
- Optimized sales strategy across online and offline channels
- Improved data storytelling and visualization for stakeholders