Dynamic Pricing and Inventory Management for Retail Store using Consumer Transactional Behavior

Paper Topic :

Data Mining

Author Name :

Vijay Patil

Abstract :

We consider a periodic inventory control model in which retail stores face problem of load of products not selling on inventory and customer interest management. To address the problem of products not selling, the system adopts a strategy, under which it calculates load factor for each product using the sales and current inventory data and suggest to create a combination of highest and lowest selling product in a subcategory to sell out the low selling product with profit. We provide a solution for dynamic pricing of products as combination. Our system removes the manual analysis part of retail chains and automates the process. To address the problem of customer interest management, system uses the transactional behavior of consumer and provides the customer with deals or offers by analyzing the trends in the history of consumer transactions. For example, Generally customers of retail stores are notified of all the offers through messages or emails which amounts a lot of notifications and so remains unattended which costs the firm a lot of money. Instead of this we can analyze the transactional behavior of the customer and suggest only with the offers that the customer might be interested in. In this way notifications get reduced so there is very low chance that our messages go unattended. It has a very high probability of customer visiting back at store to avail the offer because it is derived out of trends in customer behavior of purchasing products.

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