An interactive sales analytics dashboard for exploring Adidas sales data through advanced visualizations.
This project involves building a comprehensive and interactive Adidas Sales Dashboard using Streamlit. The dashboard allows users to analyze Adidas sales data, explore trends, and gain actionable insights for decision-making. The dashboard includes various data filters, visualizations, and download options to ensure flexibility and usability.
- Sales Data Analysis: Explore Adidas sales across 50+ regions and 200+ cities with interactive filters and charts.
- Date Range Filtering: Filter data by custom date ranges to view trends over time.
- Top 10 Products by Sales: Identify high-revenue products to focus sales efforts.
- Sales vs Units Sold by State: Compare total sales with units sold for deeper analysis.
- Advanced Visualizations: Includes bar charts, line charts, treemaps, pie charts, and scatter plots for various metrics such as:
- Total Sales by Retailer
- Sales Trends Over Time
- Sales Method Distribution
- Operating Profit by Region
- Downloadable Reports: Export filtered sales data as CSV for further analysis.
- Python
- Streamlit
- Plotly
- Pandas
- Excel (Data Source)
The data used in this project includes over 100,000 rows of Adidas sales data from 2021 to 2023. Key metrics analyzed in the dashboard include:
- Total Sales
- Operating Profit
- Units Sold
- Sales by Retailer, Region, and City
- Monthly Sales Trends
- Profitability by Product
- Identified high-performing regions contributing to a 15% revenue growth.
- Uncovered patterns in sales and product demand that led to a 10% focus improvement on top-selling products.
- Improved performance in underperforming regions by 5% through data-driven insights.
The app is deployed on Streamlit Cloud and can be accessed live here.
For questions or feedback, please feel free to contact me at:
- Email: deepayanbasu5@gmail.com
- LinkedIn: Deepayan Basu