BackBRAJESH KUMAR
02 — Case Study
Vrinda Store Annual Report 2022
A full-year view of e-commerce performance across platforms — what sold, where, and to whom.
Power BIExcel
Dashboard Preview
[ADD INFORMATION: Upload dashboard screenshot here]
01
The Problem
Vrinda Store operates across multiple e-commerce platforms (Flipkart, Amazon, and others). Without a unified view of annual sales data, it is difficult to understand which platforms drive growth, which product categories perform best, and how the business is progressing year-over-year.
02
The Dataset
Source
[ADD INFORMATION: Dataset source — e.g., Internal sales records / Kaggle]
Type
Sales transaction data (Excel/CSV)
Approximate Size
[ADD INFORMATION: Number of rows — e.g., ~31,000 orders]
Key Fields
Order IDPlatformProduct CategorySales AmountOrder DateCustomer State[ADD INFORMATION: Additional fields]
03
Objectives
- 01Track overall sales performance for the year 2022
- 02Compare sales volume and revenue across platforms (Amazon, Flipkart, etc.)
- 03Identify top-performing product categories
- 04Understand geographic distribution of orders
- 05[ADD INFORMATION: Additional questions explored]
04
Data Cleaning
- ◆Removed duplicate order records
- ◆Standardized platform and category naming conventions
- ◆Created date hierarchies for monthly trend analysis
- ◆[ADD INFORMATION: Specific Excel/Power BI transformations]
05
Key Insights
01
[ADD INFORMATION: Top platform finding]
[ADD INFORMATION: Which platform contributed most to sales and by how much]
02
[ADD INFORMATION: Category or seasonal trend]
[ADD INFORMATION: Best performing category or time period and what drove it]
03
[ADD INFORMATION: Geographic insight]
[ADD INFORMATION: Which states or regions drove the most orders]
06
Business Recommendations
- 01[ADD INFORMATION: Platform strategy recommendation]
- 02[ADD INFORMATION: Inventory or marketing recommendation based on findings]