Business Case: Data Mining and Association Rule

In the current competitive retail business, traditional brick$-$mortar business model has slowly

lost out to e$-$commerce. When trading is done online, it$$s important to understand customer

buying patterns. In return, the ability to predict this pattern into potential marketing solutions

to increase sales and profit. Business owners need to know their customers and understand

their needs and behaviors. In current business settings, customers purchasing patterns are

recorded within big data. Big data when adequately used serve good and formidable business

competitive advantage. To do this, retailers use a technique called market basket analysis.

Market basket analysis consists of analyzing large data sets that include purchase history,

revealing product groupings, and products that are likely to be purchased together.

The simulated case $($see table $1)$ below illustrates a retail purchasing pattern for garments

collected over $19$ cluster retails. The recorded purchasing combination serves to provide data

analytics to predict future marketing patterns. The key question in the market basket analysis

is what products are most frequently purchased together.