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rfm
2017 Oct 11
0
RFM analysis
...ollowing breaks, I will
generate NA values in all three scores:
df.rfm2<-qdrfm(df,rbreaks=c(10,30,50),fbreaks=c(1,2,3),
mbreaks=c(8,14,400),finish=as.Date("2017-08-31"))
head(df.rfm2)
As I wrote before, the breaks _must_ cover the range of values if you
want a sensible analysis:
df.rfm3<-qdrfm(df,rbreaks=c(0,75,150),fbreaks=c(0,2,5),
mbreaks=c(0,75,150),finish=as.Date("2017-08-31"))
head(df.rfm3)
Looking at df.rfm3, it seems that the recency score is the only one
discriminating users. This suggests to me that the data distributions
are causing a problem. First, you...