Here, we clearly observe that Segment2 has a high proportion of ProductA commands versus other markets
This might be fascinating. As much as fifty% from Segment2 purchased ProductA very first, if you’re part 4’s typical first get was ProductD. Various other area that may be of interest, but In my opinion maybe not in this case, ‘s the mean-time patch. They plots of land an average “time” invested for the for every condition. Because the we are not date-oriented, it will not make sense, but I is to suit your planning: > seqmtplot(seq, classification = df$Cust_Segment)
To manufacture the second, only indicate “day
Let’s complement the before code and look after that during the transition from sequences. Which password produces an object of sequences, next narrows you to down seriously to those individuals sequences with an experience from at the least 5%, following plots of land the big 10 sequences: > seqE subSeq spot(subSeq[1:10], col = “dodgerblue”)
