Credit Card Spending Analysis

Process:

To begin the process, I performed ETL operations, addressing duplicate values, blank/nan values, and ensuring the totals are accurate. I then created the data model and commenced data exploration.

I crafted key questions to guide my analysis:

• What trends are prevalent?
• How are customers spending their money? (Payment type)
• Are there any outliers in the data?
• Are there irregularities in customer spendings?
• On what are they spending their money? (Product category)
• How does age, gender, and marital status affect their spending?
• What percentage of their average income are they spending? (Utilization Percentage)
• Are external factors influencing their spending? (Festival deals, Special discount sales)
• How can we convert low-value customers into high-value customers?
• How can we encourage more people to use their credit cards?
• What challenges are we currently facing, and how do we plan to address them?

I tried to address most of these questions through the dashboard.

KPI's I have used

1. APST (Average Spending Per Transaction) :This KPI measures the average amount spent in a single transaction
2. APSC (Average Spending Per Customer) : This KPI calculates the average spending across all transactions for a single customer.
3. AUP (Average Utilization Percentage) : This KPI represents the average percentage of a customer's income is utilized.
4. Monthly APSC (Monthly Average Spending Per Customer) : This KPI calculates the average spending per customer on a monthly basis.

Challenge Facing Right now:

Low Credit Card Usage Across High APSC Categories:

Challenge: Encountering lower credit card usage in high Average Spending Per Customer (APSC) categories, especially in local groceries and food stalls.

Solution: Propose initiatives to transition from UPI and debit cards, offering merchants payment systems and guidance. Address concerns by partnering with businesses, providing incentives, and introducing exclusive deals on food and groceries.

Converting Lower APU Customers to Higher APU Customers:

Challenge: Transforming lower Average Utilization Percentage (APU) customers into higher APU segments.

Solution: Provide budget planners, spending insights, and introduce temporary AUP-based rewards like bonus miles to encourage responsible card usage and boost overall expenditure.

Product Recommendations:

Mitron Bloom:

Targeted Audience: Females

Features: Wellness points at spas, fashion cashbacks, extended warranties on gadgets.

Mitron Thrive:

Targeted Audience: Singles

Features: Food delivery rewards, entertainment discounts, discounts on electronics.

Mitron Legacy:

Targeted Audience: Families

Features: Groceries cashback, bills rewards, joint travel packages.

Mitron Wisdom:

Features: Discounts on medical appointments, health supplements, and fitness trackers.

Feature Recommendations:

Lifetime free credit card with no annual or joining fee.

5% cashback on grocery purchases (up to Rs.1000 per month).

1% fuel surcharge waiver on fuel spends at petrol pumps nationwide.

3x reward points on online grocery spends.

5x reward points on online dining spends.