An online retail company is looking to interpret its data to help make key business decisions. They want you to use exploratory data analysis on their transactional data, which contains information about customer purchases, including product details, quantities, prices, and timestamps. Your task is to explore and analyze this dataset to gain insights into the store's sales trends, customer behavior, and popular products, in order to help drive business decisions.
- Data Loading and Cleaning,
- Data Transformation,
- Descriptive Statistics,
- Data Visualization,
- Data Aggregation and Grouping, Outlier Detection
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Sales Trend Identification: the busiest months and days of the week, provide valuable insights for inventory management and staffing decisions.
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Top-Selling Products and Countries: can inform marketing strategies and product development efforts.
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Customer Segmentation: the business can tailor promotions and loyalty programs to target high-value customer segments.
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Anomaly Detection: Investigating outliers can help identify potential operational inefficiencies or areas for improvement.
By combining these techniques, this project provides actionable insights into online retail performance. The findings can be used to optimize operations, improve customer satisfaction, and ultimately, drive business growth.