This project focuses on analyzing e-commerce sales data to uncover valuable business insights related to sales performance, customer behavior, product trends, and profitability. The analysis was performed using data analytics techniques and visualization tools to support data-driven decision-making.
- Analyze overall sales performance
- Identify top-performing products and categories
- Understand customer purchasing behavior
- Track profit and revenue trends
- Discover regional sales performance
- Create interactive dashboards for visualization
- Excel
- Power BI
The dataset contains e-commerce transaction details such as:
- Order ID
- Product Category
- Sales Amount
- Profit
- Quantity
- Customer Segment
- Region
- Order Date
- Identified the highest revenue-generating product categories
- Analyzed monthly and yearly sales trends
- Found regions with the highest and lowest sales performance
- Compared profit margins across different categories
- Detected customer purchasing patterns
- Data Collection
- Data Cleaning & Preprocessing
- Exploratory Data Analysis (EDA)
- Data Visualization
- Dashboard Creation
- Business Insights & Conclusions
- Sales Overview Dashboard
- Profit Analysis
- Region-wise Performance
- Category-wise Sales Comparison
- Interactive Filters & Slicers
The project helps businesses:
- Improve sales strategies
- Understand customer preferences
- Optimize product performance
- Make better business decisions using data insights
- Predict future sales using Machine Learning
- Customer Segmentation Analysis
- Real-time dashboard integration
- Recommendation system implementation
Saptha M N Aspiring Data Analyst | Business Analyst Enthusiast
📧 Email: sapthamn2@gmail.com 🔗 LinkedIn: linkedin.com/in/saptha-m-n-262987332
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