📊 Shield Insurance Analysis

📕 Table of Contents

• Problem Statement
• Objective
• Tools Used
• Key Findings
• Recommendations
• Project Presentation
• Project Learnings
• Dashboard

❓Problem Statement

Shield Insurance needs to gain deeper insights into their customer base, revenue generation, and policy trends to make data-driven decisions and improve business performance. The company lacks a comprehensive understanding of customer demographics, sales channels effectiveness, and age-group impacts on their insurance products.

🎯 Objective

• Develop interactive dashboards for efficient analysis of key metrics across various dimensions (sales mode, age group, city, month, policy ID).
• Analyze customer growth and revenue trends on a daily and monthly basis.
• Evaluate the effectiveness of different sales modes in customer acquisition and revenue generation.
• Investigate age group influences on expected settlements, sales mode preferences, and policy choices.
• Provide actionable insights to support informed business decisions and strategy development.

🛠️ Tools Used

• Analytical & Visual: Microsoft Power BI
  
• Presentation: Microsoft Power Point
  

🔎 Key Findings

1. Total revenue is $989M with daily revenue growth of 15.49%.
2. Customer base of 26.841K with daily customer growth of 13.36%.
3. February to April Revenue and Customer is higher.
4. Delhi NCR and Mumbai are top in Revenue and total customer.
5. Age group 31-40 has most revenue & customer for the.
6. Offline agent is top performing sales mode. Generates more than 3 times revenue than online app which is in overall 2nd position.
7. Online-website has higher sales and customer on peak months. It takes 2nd position on peak months.
8. POL2005HEL most revenue generating and POL4321HEL has most customers.
9. POL2005HEL is popular among 65+ age group.
10. Most revenue generating age group is 31-40 and 65+ but according to most customers 41-50 is on 2nd spot.
11. Estimated settlement amount is 590M with age group 31-40 and 65+ on top.

💡 Recommendations

1. Seasonal Strategy: Capitalize on February-April peak; plan targeted campaigns and resource allocation.
2. Urban Focus: Strengthen presence in Delhi NCR and Mumbai; explore expansion in other major cities.
3. Age-Targeted Marketing: Develop tailored campaigns for the 31-40 age group to maximize revenue potential.
4. Sales Channel Optimization:
   • Invest in offline agent training and support
   • Improve online app user experience
   • Enhance website performance for peak months.
5. Product Refinement: Analyze POL2005HEL's success factors; adapt POL4321HEL to increase its revenue generation.
6. Senior Market: Create specialized products and marketing for the 65+ age group.
7. Customer Retention: Implement loyalty programs for the 41-50 age group to boost their revenue contribution.
8. Growth Management: Develop strategies to sustain the high daily growth rates (13.36% customers, 15.49% revenue).
9. Risk Assessment: Prepare for high settlement demands from 31-40 and 65+ age groups; adjust pricing and reserves accordingly.

📌 Project Presentation

Video Presentation

Slides

The detailed presentation slides for this project can be found here

🧠 Project Learnings

1. Data Loading and Transformations.
2. Power Query and DAX.
3. Data Modeling.
4. Conditional and calculated column.
5. KPI Development.
6. Dynamically switch title in visuals.
7. Implementation of dynamic filtering to analyze metrics (e.g., revenue, total customer) across different dimensions (city, age group,sales mode etc.)
8. Data visualization.
9. Data storytelling.
10. Sharpened analytical and problem-solving abilities.
11. ctionable Insights Generation.
12. Strengthened strategic planning and presentation skill.
13. Enhanced communication skills.

📈 Dashboard

• Live Dasboard