Market Basket Analysis
Learn the fundamentals of market basket analysis. Discover how to apply association rules to understand customer behavior and improve sales strategies with AI-driven insights.
At a Glance
Market basket analysis is a data mining technique used by retailers to boost sales and analyze customers’ purchasing patterns. In this project, you will perform a market basket analysis for “The Bread Basket,” a bakery located in Edinburgh. The data set has 20507 entries, over 9000 transactions, and 4 columns.
All modern companies, including online stores, analyze customer transactions and use them to form a market basket, which is actually a set of popular products that are bought together.
This basket can be used to create recommendations for shopping, product ranges, promotional offers, and placement on supermarket shelves.
This basket can be used to create recommendations for shopping, product ranges, promotional offers, and placement on supermarket shelves.
Market basket analysis is a powerful tool for turning a huge number of customer transactions into simple, easy-to-visualize rules used to promote a product and build sales recommendations.
What you will learn
In this project, we will perform the analysis of the market basket using both classical methods of data visualization and the Apriori algorithm. The analysis will also include standard indicators, rules of association, aggregation, pruning, and visualization of associative rules in the form of a dynamic graph. This project consists of the following steps:
- Download and pre-preparation data – download and change of a DataSet structure necessary for market basket analysis.
- Data Visualizations – preliminary market basket analysis.
- Association Rule – construction and analysis of associative rules.
- Visualization of Association Rules – plotting a dynamic graph that reflects the associative rules.
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