Market Basket Analysis with Recommendation Algorithms & Shiny App Implementation of a Product Recommendation System for an Online Retailer
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Updated
Oct 29, 2019 - R
Market Basket Analysis with Recommendation Algorithms & Shiny App Implementation of a Product Recommendation System for an Online Retailer
Basic Market Basket Analysis in R
Market Basket Analysis for an organization to identify the most frequently selling products in order to devise cross-selling marketing strategies using Apriori algorithm.
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Doing Market Basket Analysis using Apriori Algorithm to recommend items that are frequently bought together to do up-sale using R and deploying the model in a Shiny App.
Use of associative rule mining using the APRIORI algorithm
Market Basket Analysis is one of the key techniques used by large retailers to uncover associations between items. It works by looking for combinations of items that occur together frequently in transactions. To put it another way, it allows retailers to identify relationships between the items that people buy.
"Customers who purchased this product also purchased or viewed these products...."
Objective : Product Analysis for a store to identify the products that are frequently bought together.
This R package is used for generating automatic recommendations with association rule learning, using mined association rules from the arules package.
Market Basket Analysis and Association Rules with R
Project carried out on July 2020 for "Data Mining" (Higher Diploma in Data Analytics at National College of Ireland)
Implementation of Apriori Algorithm on Market Basket Data with Rstudio
Miscellaneous functions used in our online R courses
Academic portfolio which showcases projects completed during my graduate studies
I use R to analyze shopping transaction data, identify which supermarket items are frequently purchased together using association rule mining and the strength of those relationships, visualize the findings, and evaluate potential profit margins for different items.
The main focus of this project is to draw as many insights from the data containing transactions of the online grocery store to suggest good business ideas to the retail store in order to satisfy the customer needs and to make profits.
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