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Segregating Customers of Retail Market Based on Their Purchasing Pattern

Author(s):

Supriya V Koganurmath , Sapthagiri College of Engineering; Madhushree, Sapthagiri College of Engineering

Keywords:

Data Mining, Association Rule Mining, FP-Growth

Abstract

Retail advertisers are continually searching for ways to enhance the adequacy of their crusades. One approach to do this is to target clients with the specific offers no doubt to pull in them back to the store and to invest more energy and cash on their following visit. Demographic business sector division is a way to deal with fragmenting markets. An organization partitions the bigger business sector into gatherings in view of a few characterized criteria. Age, sexual orientation, occupation are among the generally considered demographics division criteria. A specimen contextual analysis has been done with a specific end goal to clarify the hypothesis of division connected on a retail market chain. The reason for this contextual analysis is to decide reliance on items and shopping propensities. Besides estimate deals decide the advancements of items and client profiles. Association rule mining was utilized as a technique for distinguishing clients purchasing designs and as a result client profiles were resolved. Other than Association rule, fascinating results were found about client profiles, for example, "What things do female clients purchase?" or "What do consumers (married and 35-45 matured) lean toward for the most part?".

Other Details

Paper ID: IJSRDV4I50040
Published in: Volume : 4, Issue : 5
Publication Date: 01/08/2016
Page(s): 126-128

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