| Title: | Compute Recency Frequency Monetary Scores for your Customer Data |
|---|---|
| Description: | This hosts the findRFM function which generates RFM scores on a 1-5 point scale for customer transaction data. The function consumes a data frame with Transaction Number, Customer ID, Date of Purchase (in date format) and Amount of Purchase as the attributes. The function returns a data frame with RFM data for the sales information. |
| Authors: | Satish Hariharan [aut, cre] |
| Maintainer: | Satish Hariharan <[email protected]> |
| License: | GPL-2 |
| Version: | 1.0.0 |
| Built: | 2025-01-31 03:07:58 UTC |
| Source: | https://github.com/cran/didrooRFM |
The function calculates the RFM value of a given customer data.The function consumes customer data in a fixed format and returns RFM values and scores for each customer. Click here for an overview document Click here for a VIDEO TUTORIAL
findRFM(customerdata, recencyWeight = 4, frequencyWeight = 4, monetoryWeight = 4)findRFM(customerdata, recencyWeight = 4, frequencyWeight = 4, monetoryWeight = 4)
customerdata |
- A data frame of the follwing coloumns - TransactionID, Customer ID, Date of Transaction (in date format),Amount of purchase |
recencyWeight |
- Weight the model should assign to the recency factor |
frequencyWeight |
- Weight the model should assign to the frequency factor |
monetoryWeight |
- Weight the model should assign to the monetory factor |
A data frame summarized ar customer ID level with the folloiwng data :
Individual Recency, Frequency and Monetary Scores for the data set
Weighted individual Recency, Frequency and Monetary scores for the data set
Final RFM and Weighted RFM scores for each customer
Customer class on a 5 point scale
TransNo <- c('0','1') CustomerID <- c('Cust1','Cust2') DateofPurch <- as.Date(c('2010-11-1','2008-3-25')) Amount <- c(1000,500) customerData <- data.frame(TransNo,CustomerID,DateofPurch,Amount) findRFM(customerData)TransNo <- c('0','1') CustomerID <- c('Cust1','Cust2') DateofPurch <- as.Date(c('2010-11-1','2008-3-25')) Amount <- c(1000,500) customerData <- data.frame(TransNo,CustomerID,DateofPurch,Amount) findRFM(customerData)