To analyze the sales data of Krishna Store and create an insightful Excel dashboard that helps to identify trends and opportunities for boosting sales.
-
Data Cleaning: Cleaned data by removing unwanted columns, transforming data types, and handling undefined, duplicate, or null values.
-
Data Processing: Created new columns based on existing data by using Power Query to enhance analysis .
- Age Group: Categorized as Teenager (18-29), Adult (30-49), Senior (50 and 50+).
- Month: Extracted Month from Date of order.
- Age Group: Categorized as Teenager (18-29), Adult (30-49), Senior (50 and 50+).
-
Data Analysis:
- Created pivot tables and pivot charts to visualize sales by gender, age group, category of product, and channel through which order is placed.
- Slicers for Month, Channel, and Category were also created to enable users to interact with the dashboard and view specific subsets of data.
- Created pivot tables and pivot charts to visualize sales by gender, age group, category of product, and channel through which order is placed.
-
Interactive Dashboard: Designed and formatted the dashboard with charts, shapes, and slicers.
Krishna.Store.Sales.Dashboard.mp4
- Women are more likely to buy compared to men (≈65%)
- Maharashtra, Karnataka, and Uttar Pradesh are top 3 states (≈35%)
- Adult age group (30-49) is max contributing (≈50%)
- Amazon, Flipkart and Myntra channels are max contributing (≈80%)
Target Women customers of age group 30-49 years living in Maharashtra, Karnataka and Uttar Pradesh by showing ads/offers/coupons available on Amazon, Flipkart and Myntra.