Increase Cross Selling and Up selling of Products and Services
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
Prerequisites and Target Audience
What will students need to know or do before starting this course?
- MS Excel or any other spreadsheet program
- Programming Language R
- An IDE for R called R Studio. R is free, and can be installed by downloading from (https://cran.r-project.org/). After installing R, a free version of R Studio can be downloaded from (https://www.rstudio.com/products/rstudio/download/).
- Basic Knowledge of any programming language is required for one of the sections. R language knowledge is preferred, but not necessary.
- System Requirements: Any Windows (7 or higher) or Mac machine with at least 4 GB of RAM (needed for the R example) is sufficient for this course.
- Data Sets: All data sets for the examples will be provided in MS-Excel and CSV file.
Who should take this course? Who should not?
- Marketing professionals in any industry
- Advertising and promotional managers in the retail industry
- Merchandising managers in the retail industry
- Store managers
- Financial analysts
- Lectures 32
- Quizzes 0
- Duration 7 hours
- Skill level All levels
- Language English
- Students 0
- Certificate No
- Assessments Yes
Module 1: 1. Course Overview and Objectives
Module 2: Retail Industry Overview
Module 3: Analytical Techniques in Retail
Module 4: Association Rule Mining
Module 5: Excel Example
Module 6: R Code
Module 7: Applications in Other Industries
Module 8: Summary and Next Steps
Module 9: References
Module 10: Handouts