Skip to content

"RFM Analysis" is a part of Marketing Analysis and is used to analyze customer value, thereby helping businesses to analyze each customer group they have, from there marketing campaigns or special care.

Notifications You must be signed in to change notification settings

iposoon/RFM-Analysis

Repository files navigation

[PYTHON] RFM Analysis

I. Introduction

1. About RFM Analysis

Why RFM?

  • RFM is a marketing analysis technique that stands for Recency, Frequency, and Monetary Value.
    • Recency: measures how recently a customer has made a purchase.
    • Frequency: measures how often a customer has made purchases.
    • Monetary Value: measures the total amount of money a customer has spent on purchases.
  • RFM is used to identify and categorize customers based on their purchasing behavior and how recently and frequently they have made purchases, as well as the monetary value of those purchases.

How?

  • In RFM analysis, customers are scored based on three factors (Recency - how recently, Frequency - how often, Monetary - how much), then labeled based on the combination of RFM scores

Reference

2. Business Questions

  • The Marketing Department needs to classify the segments of each customer to deploy each marketing program suitable for each customer group.
  • The Marketing Director also proposed a plan to use the RFM model in Python to segment customers, and then launch marketing campaigns to thank customers for supporting the company over the past time. As well as exploit potential customers to become loyal customers.
  • Suggestions to the Marketing and Sales team with the company's retail model, which of the three indicators R, F, and M should be most interested in?

II. Data Visualization with Python

  • Seaborn Countplot of Frequency

image

  • Treemap of customer segmentation

newplot

  • Seaborn Countplot of customer segmentation

image

  • Pie chart of Channel

image

  • Pie chart of Ship mode

image

  • Pie chart of Category

image

  • Pie chart of Sub-category

image

  • Bar plot: Total Sales by Segmentation

image

  • Bar plot: Total Profit by Segmentation

image

  • Bar plot: Total Sales by Region

image

  • Treemap of State by Orders

newplot (1)

III. Insights

  • 1.The most important index of the 3 indicators that the SuperStore company needs to pay attention to is F, then R: because the rate of customers buying once and twice is very high. Very few customers make long-term purchases like 8-9 times or more. -> That shows that the customer retention rate at the company is still low.

  • 2.About Customer Segmentation: The company is mainly "New Customers" >"Hibernating customers">"Lost customers". -> This again shows that we need to pay attention to the index F.

  • 3.Revenue and profit from "New Customers" is the highest.

  • 4.The revenue in the East region is the lowest compared to the other 3 regions.

  • 5.California, Texas, Illinois vs Florida are the states with the most orders.

  • 6.The company's main customers are Consumers accounting for 52%, Corporate: 30% and finally Home Office.

  • 7.The categories with the most orders are "Office Supplies" up to 60%, then "Furniture".

  • 8.The main subcategory are: Paper(14%), Binders(15%), Art(9%), Phones and Storage (8%).

IV. Recommendations

  • The company needs to have policies to:
    • Retaining new customers:
      • For new customers who have made a recent purchase, send a personalized welcome email or offer that thanks them for their purchase and encourages them to return to our business.
      • For customers who have made only one purchase, use email marketing to keep them engaged with our brand and encourage them to make a second purchase.
      • Offer a special discount or promotion to incentivize them to return.
      • For customers who have made a high-value purchase, thank them for their business and offer a loyalty program that rewards them for their continued purchases.
    • Promoting hibernating customers:
      • For hibernating customers who have not made a purchase in a while, send a win-back email or offer that encourages them to return to our business.
      • Offer a special discount or promotion that is personalized based on their past purchases.
      • For customers who have made multiple purchases in the past but have not made one recently, send personalized email campaigns that showcase new products or services that may be of interest to them.
      • For high-value customers who have not made a purchase in a while, send a personalized email or offer that highlights new products or services that may be of interest to them and offer a special discount or promotion that is tailored to their past purchase history.
  • Need to have a marketing strategy to focus on the segment: Consumer -> Office Supplies segment in states like California, Texas, and Illinois vs Florida.

About

"RFM Analysis" is a part of Marketing Analysis and is used to analyze customer value, thereby helping businesses to analyze each customer group they have, from there marketing campaigns or special care.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published