Content:
RFM analysis is a technique for categorizing customers based on their purchasing behavior. This segmentation method allows marketing teams to target customers with personalized marketing campaigns. Instead of analyzing the entire customer base as a whole, it's better to segment them into homogenous groups, understand the traits of each group, and engage them with relevant campaigns.
RFM stands for Recency, Frequency, and Monetary value. That means we have to use these metrics in order to perform this method. So what are these values?
- Recency : The freshness of customer activity. It's the time difference between the last purchase date of the customer and the date of analysis.
- Frequency : The frequency of the customer transaction, means a total number of transactions.
- Monetary : Sum of each purchase that has been made by each customer.
- Who are your best customers?
- Which customers have a chance to churn?
- Who has the potential to become valuable customers?
- Who are your loyal customers?
- Who are your new customers?
- Which customers is critical to retain?
- Which group of customers is most likely to respond to your current campaign?
- Which customers are lost?
and more
- This Online Retail II data set contains all the transactions occurring for a UK-based and registered, non-store online retail between 01/12/2009 and 09/12/2011.The company mainly sells unique all-occasion gift-ware. Many customers of the company are wholesalers.
- Invoice: Invoice number, unique identifier variable for each transaction. Refund invoice numbers starts with "C"
- StockCode: Unique product code
- Description: Product name
- Quantity: The number of product in the invoice
- InvoiceDate: Date and time of the purchase
- Price: Unit price of a product (in terms of Sterlin)
- CustomerID: Unique customer identifier
- Country: Residential country of customers
- We want to segement the Customers based on RFM so that the company can target its customers efficiently.