Analysis of shopping behavior of clients of an internationally active supermarkets
Problem statement:
- Our client wanted to understand baskets of products customers tend to buy together, depending on their age, gender, purchasing power along with other characteristics such as weather, time of the day, month or year.
Dataset:
- The dataset consisted of approximate 5 million transactions, 600,000 receipts and 10,000 customer card holders.
Our approach:
- Advanced mathematical models based on Class Association Rules developed in-house using SCALA/ MongoDB and R were used for this specific project.
- Visualization of the results was done using java scripts.
