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RFM Analysis for Customer Segmentation

• Who are my best customers?

• Which customers are at the verge of churning?

• Who has the potential to be converted in more profitable customers?

• Who are lost customers that you don’t need to pay much attention to?

• Which customers you must retain?

• Who are your loyal customers?

• Which group of customers is most likely to respond to your current campaign?

Through RFM analysis we are able to answer these questions and make the right decisions for our business

What RFM Analysis is?

RFM analysis is a data-driven segmentation technique that uses Recency, Frequency and Monetary to divide customers into various categories or clusters and identify who are more likely to respond to promotions and also for future personalization services. These RFM metrics are important indicators of a customer’s behavior because frequency and monetary value affects a customer’s lifetime value, and recency affects retention, a measure of engagement.

• Recency - How recently a customer has made a purchase

• Frequency - How often a customer makes a purchase

• Monetary - How much money a customer spends on purchase

Tableau packaged workbook file

• RFM Analysis for Customer Segmentation.twbx
• Go to my Tableau Public Page following the link https://public.tableau.com/views/IMDB_ONE_PIECE/Dashboard?:language=it-IT&:display_count=n&:origin=viz_share_link
  
  
  

Dataset

• Customer Segmentation - RFM.xlsx file
• https://www.kaggle.com/carrie1/ecommerce-data