Optimization system and optimization method

An optimization system comprising:

• a sales data acquisition unit that is configured to be able to acquire sales data of a permanent store when a store opens and sales data of the permanent store when the store does not open;
• a sales data difference acquisition unit that is configured to be able to acquire a difference between sales data of the permanent store when a store that opens only for a limited period of time opens and sales data of the permanent store when the store does not open, based on the data of the sales data acquisition unit;
• a store attribute information acquisition unit that is configured to be able to acquire one or more items of store attribute information for classifying feature of the store;
• a model training unit that creates a correlation model for a sales data difference and the store attribute information by using the sales data difference and the store attribute information as inputs;
• and
• a trained model storage unit that stores the created model,
• wherein information regarding one or more store tenants is presented in such a way as to increase a sales difference based on the model.

An optimization method for a store combination for presenting an optimal combination of stores to be opened, the optimization method comprising:

• a first step of acquiring touring of stores by a customer;
• a second step of acquiring one or more items of store attribute information for classifying features of the stores;
• a third step of creating a correlation model for the touring by the customer and the store attribute information by using the touring of the stores by the customer and the store attribute information as inputs;
• and
• a fourth step of presenting information regarding one or more stores to be opened in such a way as to increase the touring of the stores by the customer based on the model.

An optimization method for a store combination for presenting an optimal combination of stores to be opened, the optimization method comprising:

• a first step of acquiring sales data of a permanent store when a store to be opened opens and sales data of the permanent store when the store to be opened does not open;
• a second step of acquiring one or more items of store attribute information for classifying features of the stores;
• a third step of creating a correlation model for a sales data difference between sales data of the permanent store when a store that opens only for a limited period of time
• opens and sales data of the permanent store when the store does not open, and the store attribute information by using the sales data difference and the store attribute information as inputs;
• and
• a fourth step of presenting information regarding one or more stores to be opened in such a way as to increase a sales difference based on the model.