• Shreyash S. Mane
• Shweta M. Barhate
• Satish J. Sharma

In India, there are number of entrepreneurs or retailers, who have started their own business or launched their own products. The major difficulty that they were facing is marketing. They spend a lot of money on marketing but do not get an appropriate result as they are not aware about their probable customer, details of the customer, preferability about their products, etc. So, they couldn’t achieve much success be it increase in sales, customer satisfaction, etc. Study of customer behavior in retail stores usually deals with identification of customers and their buying behavior patterns. All the activities of the business concerns end with customer attraction and customer satisfaction. Customer behaviour analysis has become an integral part of strategic market planning. To perform the customer behaviour analysis we used an association rule mining and clustering. Association rule mining identifies relationship between a large set of data items. Using association rule mining associativity between two products is made effectively so that the associated item is bought along with the most frequent bought products. Clustering is a technique which forms a group of similar data. Using Clustering technique, we get the cluster of most purchased product. This will help the entrepreneurs, retailers for making marketing strategies and increase product sales to achieve high levels of customer satisfaction. The study was carried out with the help of data mining techniques on retail_dataset.csv. The experimental work is done in weka software.

Data Mining, Association rule mining, Apriori algorithm, Clustering, Simple K-Means algorithm

"CUSTOMER BEHAVIOUR ANALYSIS USING DATA MINING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.13-16, June-2022, Available :http://www.jetir.org/papers/JETIRFM06003.pdf

"CUSTOMER BEHAVIOUR ANALYSIS USING DATA MINING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. pp13-16, June-2022, Available at : http://www.jetir.org/papers/JETIRFM06003.pdf