Abstract
Data mining is one of the most essential tools for gathering information from different datasets in almost all recent industries. In this 21st-century, data mining gained attention because of its significance in decision making, and it has become a key component in various industries such as retail. Inventory management requires pre-planned goals and attention to detail, and prioritizing items that require less attention can be a waste of time and resources. Learning indications about customers’ shopping patterns by showing associations among various provides significant value in managing retail inventory. In the present research paper, popular data mining techniques have been applied and analyzed for multi-item inventory management in retail sales stores to show how data mining techniques can optimize and organize the retail inventory.
Highlights
In the last few years, the internet gives us new business concepts and much information
Inventory management is one of those key sectors that determine the success of a retailer
Mining or extracting customer insight from structured and unstructured data and other sources is of Customer relationship management (CRM) aims at stronger loyalty of customers with feasible market share
Summary
In the last few years, the internet gives us new business concepts and much information. The application of data mining process in customer’s behavior becomes a excellent tool. With increased globalization and advancement in technology, the retail market has become more and more dynamic, and retailers need a new approach to identify different objectives to be more competitive and successful. Inventory management is one of those key sectors that determine the success of a retailer. Mining or extracting customer insight from structured and unstructured data and other sources is of Customer relationship management (CRM) aims at stronger loyalty of customers with feasible market share. With competition for shelf space intensifying, there is a pressing need to provide shoppers with a highly differentiated value proposition through “right product mix in the right amount at the right time.” [7]
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