Download the dataset below to solve this Data Science case study on Market Basket Analysis.
Market Basket Analysis is a data-driven technique used in retail and e-commerce to uncover patterns of co-occurring items in transactions. It aims to identify relationships between products that are frequently purchased together, providing valuable insights for product placement, cross-selling, and marketing strategies.
The dataset provided contains transactional data, with columns representing:
- BillNo: A unique identifier for each customer’s bill.
- Itemname: The name of the purchased item.
- Quantity: The quantity of the item purchased.
- Price: The price of each item.
- CustomerID: A unique identifier for each customer.
Perform a Market Basket Analysis on the given dataset to discover associations between purchased items. Specifically, the goal is to identify:
- Which items are frequently purchased together by customers.
- The strength of these associations (e.g., support, confidence, lift).