Course Description

In this course, students will learn to segment customers using recency, frequency and monetary value analysis. Students will look at a case study to understand how RFM can be used to segment customers and tailor offers to them. They will understand the difference between transaction level data and customer level data. What data must be available to carry out RFM analysis? How are the scores calculated? How to define customer segments using RFM score? How to visualize and interpret the output from RFM analysis? How to use the output to design custom offers to customers to reduce customer churn and improve average order value.

Self Paced Online Courses


Our online self paced courses are designed to allow participants to learn at their convenience. Learning outcomes are clearly defined and enhanced by the use of byte sized videos, PPTs, assignments, quizzes, suggested reading and case studies. Participants can take advantage of the discussion forum to discuss with their peers and the instructors to enhance their learning experience.


Course Features



Course Requirements

  • Access to a computer with an internet connection

  • Ability and permissions to download files & install software

  • Basic knowledge of English (Course is delivered in English language)


Who is this course for?


We expect the students to have some prior experience with R and RStudio. If you have never used R before, our Introduction to R course will help you prepare for this course.


If I do not meet the requirements to enroll, what should I do?

We have a number of free courses that can help you prepare including:

  • Introduction to R

  • Import Data into R

  • Data Wrangling with dplyr



How will I execute the practical's?


You will use RStudio for the practical's. All the R scripts used in the examples, assignments and case study are available for download from the Learning Management System. For those of you who face issues installing RStudio on your system, we have created a RStudio cloud project where you can practice without installing any software or downloading files.


Do I need to apply? What are the admission criteria?

No. This course is open to enrolment for all and accepts students regardless of experience and background.


Course curriculum

  • 1

    Course Materials

    • Welcome

    • Agenda

    • Slides

    • R Script

    • Resources
  • 2

    Case Study Overview

    • Overview
  • 3

    RFM Concepts

    • Introduction

    • Applications

    • RFM Table

    • RFM Metrics

    • Recency

    • Frequency

    • Monetary Value

    • Compute Monetary Score

    • Compute Frequency Score

    • Compute Recency Score

    • RFM Score

    • Define Segments
  • 4

    R Session (Demo)

    • Introduction

    • Transaction & Customer Level Data

    • Generate RFM Table

    • Customer Segmentation

    • Distribution of Segments

    • Visualize Recency, Frequency & Monetary Value of Customer Segments

    • Other Plots & Tab Completion
  • 5

    Shiny Web Application

    • Shiny App Demo
  • 6

    Summary

    • Your Turn

    • Practice

    • Thank You

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