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RFM Customer Segmentation

  • (3)   336 viewers

Free

Learn the principles of RFM analysis and explore an RFM analysis dashboard from a real-world business.
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/images/avatar/kvyzas.webp   /images/avatar/ioanik.webp   /images/avatar/chrismaragkakis.webp  
Available in
  • Practical
  • No Sign-Up Required

Overview

RFM Segmentation Analysis is a data-driven customer segmentation technique used by businesses to understand and categorize their customers based on their past purchasing behavior.

The primary objective of RFM analysis is to efficiently identify and target distinct customer segments for marketing campaigns, aiming to retain valuable customers, engage existing ones, and re-engage those who have left.

This technique relies on three important components: Recency (days since the last transaction), Frequency (total number of transactions), and Monetary Value (total amount spent).
In this Tutorial you will be able to learn the principles of RFM analysis and explore an RFM analysis dashboard from a real-world business.


What you'll learn

1. Basics of Customer Segmentation
  • What is Customer Segmentation?
  • What are the most popular Segmentation methods.
2. Understanding RFM
  • What is RFM? The meaning of Recency, Frequency, and Monetary values.
  • When was RFM first used?
  • Are there any variations of the original RFM model?
  • Why is RFM so important?
3. Calculating RFM Scores
  • Step 1 : How to calculate RFM components?
  • Step 2 : How to assign scores to RFM components?
  • Step 3 : How to calculate the final RFM scores and segments?
4. RFM Segments and Strategies
  • Which are the most common RFM Segments and their Corresponding Strategies?
  • How to use RFM segments?


What you'll see in the Dashboard

1. RFM Overview
  • Get an Overview for RFM Segments characteristics and understand Customer behavior.
2. RFM Movements
  • Inspect the movements of RFM Segments over time using Historical RFM or RFMt.
3. Recency Analysis (Days Since Last Transaction)
  • Analyze the Recency Component.
4. Frequency Analysis (Total Transactions)
  • Analyze the Frequency Component.
5. Monetary Analysis (Total Net Revenue)
  • Analyze the Monetary Component.
6. Recommendations
  • Get recommended strategies per Customer.
7. About The Data
  • A small note about the data contributior and the data reliability.


Requirements

No prior experience is required. All you need is a computer or a tablet.

SKU RFM-CSG-TUT
Slug rfm-customer-segmentation-tutorial
Product Type Tutorials
Category Customer Segmentation
Tags RFM, Customer Segmentation
Audience Managers, Senior Marketers, Emerging Marketers & Analysts, Senor BI Analysts
Business Type Repeat Retail, Subscription Based
Data Provided By A Restaurant Chain (Anonymous Provider)
Setup Time 10'
Setup Difficulty 1 | No technical knowledge needed — Use the Browser or Spreadsheets
Tech Used CRM - Google BigQuery - Looker Studio

How to Use

Video Thumbnail

To get the most out of the Tutorial, follow these steps:

  • If you are unfamiliar with RFM Segmentation analysis concepts, or if you want to refresh your memory, start the mini-course.

  • Explore the Dashboard, read side-notes, play with the filters, and draw conclusions.

Remember, it's all about learning, exploring, and getting ideas!

Reviews

Data Analytics Expert
Pleo

Understanding RFM is the foundation for implementing any advanced customer segmentation or behavioral prediction model. The idea and the execution are excellent. Looking forward to seeing what is coming next!

Digital Marketing Manager
Humble Digital Agency

Really loved the idea, both the real-world application and the illustrations! The real-world example made RFM analysis easy to understand. Super helpful for someone like me who learns better with practical stuff. Can't wait for more tutorials like this – simple, clear, and straight to the point. Great job!

Senior Data Engineer
Mayainsights

What a great practical resource for understanding RFM and how it is used (I bookmarked it). Even though RFM is a very classic segmentation method, many of our customers often struggle to understand the basics or why this is important. I am looking forward to the release of Templates and SQL Builder to see the magic behind RFM and RFM Historical implementation.

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