Attached is a sample of creating customer journeys within R code this was using a SQL Server database as a backend.
#==========================EM Clustering on the text===============================#
#word frequency
wordFreq <- sort(rowSums(m), decreasing = T)
#String count fun
strcount <- function(x, pattern, split){
unlist(lapply(
strsplit(x, split),
function(z) na.omit(length(grep(pattern, z)))
))
}
#Find counts of each words for each record
string <- names(wordFreq[wordFreq > 40])
#Null data frame for storing
count.string <- matrix(0, ncol = length(string), nrow = length(MN1[, 1]))
count.string <- data.frame(count.string)
for (i in 1:length(string)){
count.string[, i] <- strcount(tolower(MN1[1:length(MN1[, 1]), 1]), string[i], " ")
}
colnames(count.string) <- string
#Conbind the data frame with orginal data records
MN2 <- cbind(MN1[ ,1], count.string)
#Clustering
mc <- Mclust(MN2[, 2:length(MN2[1, ])], 3)
plot(mc, what = c('classification'),
dimens = c(3, 4))
MN2.output <- MN2[mc$classification == 2, ]
