Application of Association Rule Mining in a Clothing Retail Store

Akshay Jain (), Shrey Jain () and Nitin Merh ()
Additional contact information
Akshay Jain: SVKM’s Narsee Monjee Institute of Management Studies (NMIMS)
Shrey Jain: SVKM’s Narsee Monjee Institute of Management Studies (NMIMS)
Nitin Merh: Jaipuria Institute of Management Indore

A chapter in Applied Advanced Analytics, 2021, pp 103-114 from Springer

Abstract: Abstract In this paper, an attempt has been made to understand the buying pattern of customer with the help of market basket analysis, which is an important tool in modern retailing industry. Retailing is defined as the timely delivery of goods and services demanded by end customers at prices that are competitive and affordable. Through association rule in data mining, we have tried to understand consumer behavior, brand importance, seasonality effect, buying pattern, product basket from the data. Data mining is the practice of analyzing database to gather and generate new information. Association rule mining is a process of finding rules that govern relation between sets of items. Market basket analysis is a modeling technique based upon the theory that explains the buying relation between certain groups of items. The transactional data is collected from the retail clothing store “Try Us” located in Indore, Madhya Pradesh, from the period November 26, 2017, to September 19, 2018, with the help of Point of Sale (POS) and bar code scanner. “Try Us” is a small retail store with multiple brands and is planning to upgrade store to a multilevel store. Data mining would benefit the overall store performance. Frontline Solver® Analytic Solver Data Mining (XLMiner) is used for simulations.

Keywords: Data mining; Association rule mining; Market basket analysis; Apriori algorithm (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-981-33-6656-5_9

Ordering information: This item can be ordered from
http://www.springer.com/9789813366565

DOI: 10.1007/978-981-33-6656-5_9

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().