Type: Speaker | Location: Red McCombs School of Business, University of Texas, Austin, U.S.A
This hands-on workshop laid out one of many ways to understand customer purchase behavior by looking at past retail transactions (store and/or online) and the collection of items that come together (think “association”) in a market basket (think “receipt”). This Market Basket Analysis (also known as Affinity Analysis and the technique called Association Rule Mining) is used to determine the likelihood of these items occurring together. This discovery of products and services being purchased together is used to identify specific items to be sold to specific customers, and help in increasing the customer’s lifetime value (CLTV).
Thus, retailers (and other industries) can use the knowledge and discovery about associations to
With the help of MS-Excel exercise and easy-to-understand examples, and some small R code, we quickly demonstrated how a data mining algorithm along with retail data can be really leveraged to make a positive difference to business outcomes.