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.

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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