Dashboard Link: https://app.powerbi.com/links/FXXkIZytyi?ctid=b29282ab-1dfd-4fb3-9599-e0bb2f469af8&pbi_source=linkShare
This dashboard enables businesses to understand customer segments and tailor services accordingly. By examining key demographic and transactional data, the company can identify target segments and their preferences, optimize marketing strategies, and enhance customer satisfaction. Key metrics like age groups, spending habits, and payment preferences are visualized to uncover trends, helping prioritize improvements and increase engagement among high-value customer segments.
Step 1: Data Loading - Loaded the customer dataset (CSV file) into Power BI.
Step 2: Data Quality Check - In Power Query Editor, enabled “Column Distribution,” “Column Quality,” and “Column Profile” options to analyze data quality across columns.
Step 3: Data Profiling for Entire Dataset - Set column profiling to cover the entire dataset.
Step 4: Handling Missing Data - Identified and handled missing values for accuracy in metrics calculations, especially in revenue-related columns.
Step 5: Theming - Applied a consistent theme for visual clarity.
Step 6: Customer Segmentation Visuals - Created visuals for demographic and behavioral segmentation, including “Age Group,” “Customer Type,” “Gender,” and “Region.”
Step 7: Slicers for Filtering - Added slicers to filter by customer attributes for a more detailed view of each segment.
Step 8: Spending Behavior Analysis - Created visuals showing average spending across payment methods and gender.
Step 9: Card Visuals for Key Metrics - Used card visuals to represent average revenue per customer and total revenue.
Step 10: Segmentation Insights by Age Group - Defined age groups for customers using DAX and represented them with a visual to show the revenue generated by each segment.
Step 11: Customer Count and Distribution - Created measures to calculate the total customer count and the percentage of customers within each segment.
Step 12: Publishing - Published the report to Power BI Service for easy access and sharing.
Age Group: The majority of customers are in the 25-50 age group (52%). Customer Type: 81% of customers are returning, indicating strong loyalty. Gender: A balanced distribution between male and female customers.
Payment Method: 60% of transactions are digital, reflecting a high preference for online payments. Revenue Contribution: The 25-50 age group generates the most revenue.
Regions: Highest revenue comes from the central region, highlighting a key market.
Revenue per Customer: Identifying high-revenue segments helps in strategizing personalized marketing efforts.