Retail industry has always been a pioneer in using Analytics to sell more, reduce cost of goods sold, and enhance customer experience. About 20 years ago, the retail industry in the U.S. started gravitating from a product-centric view of the world to a customer-centric view, and moved towards a more personalized, “segment of one” approach. It has taken leaps and bounds in providing exceptional customer experience at the same time, cutting costs dramatically. In this highly competitive landscape, and with dwindling margins, the need to cross and up sell to existing customers and figuring out what items to promote (or not) to attract new customers, has only grown stronger. This course will lay 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).
What am I going to get from this course?
- Increase cross-sell and up-sell of products and services
- Determine the right "Next Best Offer" to the right person and optimize marketing spend
- Apply promotion programs
- Improve loyalty and retention of the customer
- Optimize product placement
- Optimize product bundling
- Optimize the supply chain