Open AccessAnalyze and Enhance Sales in Lulu Supermarket using Data Mining Technology
Author(s) -
Ahmed Abdullah Awadh Koofan,
Mohammed Kaleem
Publication year - 2020
Publication title -
journal of student research
Language(s) - English
Resource type - Journals
ISSN - 2167-1907
DOI - 10.47611/jsr.vi.926
Subject(s) - association rule learning , hypermarket , computer science , python (programming language) , data mining , affinity analysis , data science , product (mathematics) , customer relationship management , marketing , business , database , geometry , mathematics , operating system
-Data mining is a powerful technology for analyzing huge data, it has many techniques such as; classification, clustering, prediction and association rules etc., In this research Association rule will be used for analyzing data, which will help to extract the data related to combinations of items. Numerous customers tends to purchase items regularly, each time they visit supermarket, customer’s need to move around from shelf to shelf for the product of their interest which is time consuming. This research will help to minimize the time consumption for customers by analyzing the customer’s invoices and letting know the supermarket about the patterns of customer's orientations. In this work python tool will be used for data mining, by using association rule to analyze the customer’s purchases and retrieve the relevant information which will help to determine the customer’s pattern and know the association between products. In this rationale, the data of customer’s purchases were collected from Lulu hypermarket for data analysis and the outcomes of the analysis is to know the customer’s patterns and making the shopping easy by reorganizing the related items and the most buying items together on same shelf.