Personal Project
Sales Performance Analysis
- Collect relevant data from various sources, including sales databases, CRM systems, and marketing platforms.
- Clean and preprocess the data to ensure accuracy and consistency. Handle missing or outliers appropriately.
- Identify key performance indicators (KPIs) such as sales revenue, conversion rates, customer acquisition cost, and average order value
- Create interactive dashboards and visualizations to communicate key findings using tools like Tableau, Power BI, or Python libraries like Matplotlib and Seaborn.
- Perform EDA to gain insights into the dataset. Use statistical and visual methods to identify patterns, trends, and anomalies.
- Explore relationships between different variables, such as sales and marketing channels, customer demographics, and product categories.
