Shield-Insurance-BI-Report

Table Of Contents

1. About Company
2. Tool Used
3. Dataset
4. Objective
5. Dashboard
6. Insights
7. Recommendation

🔗 Live Dashboard: View Dashboard

🎥 Presentation Link: Watch Presentation

About Shield Insurance

Shield Insurance is a forward-thinking provider dedicated to safeguarding individuals and businesses with a comprehensive suite of insurance solutions, including life, health, auto, property, and commercial coverage. Founded on principles of reliability and transparency, Shield Insurance emphasizes customer-centered solutions and consistently refines its offerings through data-driven insights.

With a strong focus on innovation and service excellence, Shield Insurance adapts to the evolving needs of its clients, empowering them to navigate the future with confidence. Its expanding customer base and growing industry impact underscore its commitment to setting a new standard in the insurance industry.

Tool Used:

• MS-Excel
• Power-BI
• PowerPoint & Canva (ppt)

📁 Dataset

The dataset provided by AtliQ Technology is from Insurance companies, in which we have to track the 5 major key metrics

📝 Tracking customer and revenue

📝 Daily revenue and customer growth rate

📝 Sales mode Analysis

📝 Trends in customer and revenue growth

📝 Age group analysis

🎯 Objective

To gain valuable insights into customer demographics, revenue generation, and the impact of sales and policy trends, this analysis focuses on the following key areas:

1. 📈 Customer and Revenue Tracking

• Measure total customers and total revenue.
• Track daily growth rates for both revenue and customer base.

2. 📊 Policy Impact Monitoring

• Analyze month-over-month policy changes to identify trends and areas for improvement.

3. 👥 Customer Segmentation and Trend Analysis

• Segment customers by age group and analyze data by city and age group.
• Toggle between revenue and customer trend graphs to assess growth patterns over time.
• Use filters for in-depth analysis by sales mode, age group, city, month, and policy ID.

4. 💼 Sales Mode Analysis

• Develop a dedicated page to explore customer demographics and revenue distribution by sales mode.
• Track monthly trends in sales mode to understand performance variations.

5. 👶 Age Group Insights

• Conduct a focused analysis on age group impact to assess settlement expectations, sales mode preferences, and policy selection trends.

📊 Dashboard

Home Page

Overall Analysis

Sales Mode Analysis

Age-Group Analysis

📊 Insights

• City-wise Revenue & Customer Distribution: Delhi NCR leads with ₹402M in revenue and 11,000 customers, followed by Mumbai (₹240M, 6,400 customers) and Hyderabad (₹161M, 4,300 customers). Chennai and Indore represent potential growth areas due to their lower revenue and customer counts.

• Revenue & Customer Distribution by Age Group: The 31-40 age group generates the highest revenue at ₹356M, indicating strong engagement. Significant contributions also come from the 41-50 (₹196M) and 65+ (₹184M) age groups, while younger demographics (18-24 and 25-30) present growth opportunities.

• Customer and Revenue Trends by Policy ID: Policy ID POL4321HEL has the highest customer count (4.4K), with March 2023 peaking at 7.1K customers. Revenue reached ₹264M in March 2023, with POL2005HEL leading in revenue at ₹324M.

• Sales Mode Analysis: Offline channels dominate customer acquisition, contributing 71.27% of total customers, with Offline Agents at 55.41%. For revenue, Offline Agents generate 55.67%, highlighting the ongoing importance of offline strategies.

• Total Customers and Revenue by Age Group: The 31-40 age group drives the highest revenue, while numbers decline with age. Focusing on tailored products for this group can boost growth.

• Settlement Rate Insights: The 31-40 age group leads with a 34.79% settlement rate, with younger groups (18-24 and 25-30) showing potential for improvement in settlements.

• Policy Optimization: Policies like POL4321HEL are essential across age groups, and optimizing these top policies can help sustain and grow market share.

💡 Recommendations

• Optimize High Revenue Policies: Invest in enhancing top-performing policies like POL2005HEL to maximize revenue and customer acquisition, while also strategizing improvements for lower-performing policies such as POL4321HEL.

• Target Key Demographics: Tailor marketing and engagement efforts specifically for the 31-40 age group, which shows strong revenue potential, while exploring growth opportunities among younger demographics (18-30).

• Enhance Offline Channels: Given the significant contributions from offline channels, strengthen support for Offline Agent and Offline Direct channels, while simultaneously improving online presence to capture digital growth.

• Timing Optimization: Capitalize on high customer and revenue peaks, particularly in March, by launching targeted campaigns to maximize engagement and optimize policy offerings.

• Age-Based Policy Customization: Create tailored policies and settlement strategies for the 31-40 age group, the largest revenue contributor, while identifying growth potential in other age groups like 18-24 and 25-30.

🙏 Thank You!

Thank you for taking the time to review this analysis and recommendations. Your feedback and insights are greatly appreciated!

📧 Contact Details

If you have any questions or would like to connect, feel free to reach out via email: [email protected]