![]() ![]() ![]() Examples, retail stores, or supermarkets. The knowledge base system primarily predicts based on the products bought together. Amazon, Netflix are great examples of recommender system usage. Based on the prediction of a buyer's preferences, it recommends a list of products that the customer is more likely to buy. ![]() The recommender system primarily collects the data of customers purchasing behavior and predicts the possibility of products bought together. It will give you a complete picture of the market basket analysis concept and objective. Based on this data or prediction a recommendation can be displayed on the e-commerce website.īefore we move on to the association rules and measures of market basket analysis, let us understand the recommender system. The objective of market basket analysis is to increase sales by identifying the products bought together by customers. Market Basket analysis also called Affinity Analysis. In other words, if a customer buys a product, what is the probability that he/she will buy another product along. Market basket analysis is a modeling method used to identify the products purchased together. Let us begin by understanding the basics of market basket analysis. Market basket analysis is the most important topic for every online or offline retail business.
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