Our client, a global retailer, offers seasonal and end-of-line deals. Therefore, the goods must leave the shelves and the department stores' before the next season starts and new goods are delivered. For this purpose, the retailer introduced a pricing strategy that lowers the prices of the products within a particular time window.
The product managers felt that the markdown strategies were wasting their time. They only wanted to approve or correct these strategies. On the one hand, the teams were overloaded. On the other hand, they chose a pricing strategy that left a big waste to empty the department stores'. Our client's data scientists wanted to create an automated solution.
