An interactive Power BI dashboard analysing sales performance, revenue drivers and cancellation impact for Ecom Express — one of India's leading e-commerce logistics and delivery companies.
The analysis focuses on identifying which products, categories and cities drive revenue, how cancellations impact overall performance, and where operational improvements can be made.
- Domain: E-commerce Sales Performance
- Company: Ecom Express
- Pages: 2 interactive dashboard pages
| KPI | Value |
|---|---|
| Total Revenue | ₹389.99M |
| Average Order Value (AOV) | ₹142.38K |
| Revenue Lost to Cancellations | ₹167.87M |
- Microsoft Excel — Data cleaning and initial data preparation
- Power BI Desktop — Dashboard development and visualisation
- DAX — Custom KPI measure creation
- Data Modelling — Table relationships and schema design
- Power Query — Data transformation inside Power BI
- Removed duplicate order records
- Handled blank and null value rows across key columns
- Standardised product category naming conventions for consistency
- Corrected date formats to ensure compatibility with Power BI time intelligence
- Cleaned and validated city names for accurate geographic grouping
- Removed invalid and test entries from order records
- Standardised column headers before importing into Power BI
- KPI cards: Total Revenue, AOV, Revenue Lost to Cancellations
- Revenue by Product Name (bar chart)
- Revenue by Category (bar chart)
- Revenue by City (bar chart)
- Revenue by Year and Quarter (line chart)
- Dynamic date and time slicer
- Product-level slicer for filtered analysis
- KPIs update dynamically based on selected product
- Category and city performance filtered by selection
- Time-based revenue trend per product
Laptops and Mobiles are dominant revenue contributors — indicating over-dependence on two product lines for majority of income. Portfolio diversification across categories is recommended.
₹167.87M lost to cancellations represents significant revenue leakage. With total revenue at ₹389.99M, cancellations are eroding nearly 43% of potential revenue — an urgent operational priority.
Clear divide between top-performing and underperforming cities visible in revenue distribution. Targeted regional sales strategies and localised campaigns could address underperforming markets.
Visible revenue gap across product categories highlights uneven portfolio performance — suggesting opportunity for category-specific promotions or inventory rebalancing.
Revenue fluctuations across quarters reveal seasonal demand patterns — useful for inventory planning, staffing decisions and campaign timing.
Average Order Value of ₹142.38K suggests high-ticket purchases dominate — Laptops and electronics likely driving this figure. Lower AOV categories may benefit from bundling strategies.
- 🎯 Diversify revenue beyond Laptops and Mobiles to reduce concentration risk
- 📦 Investigate root causes of cancellations — logistics delays, payment issues or product quality — to recover ₹167.87M revenue leakage
- 🏙️ Deploy targeted campaigns in consistently underperforming cities
- 📅 Align inventory and staffing with quarterly demand patterns
- 💰 Introduce bundling strategies for lower AOV product categories
- 📊 Monitor product-level cancellation rates separately to identify highest-risk SKUs
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ecom-express-sales-analysis/ │ ├── data/ │ └── ecom_express_cleaned.xlsx ├── dashboard/ │ └── EcomExpress_Sales_Analysis.pbix ├── screenshots/ │ ├── page1.png │ └── page2.png └── README.md