This post is based on a project where we needed to see how many transactions we were actually missing in Google Analytics.
The how to
This process is quite simple, we will be pulling out transaction id’s and then make it into a list. After that we compare that list with another
ga_id <- "yourgaid" data <- google_analytics(ga_id, date_range = c("2019-01-23", "2019-02-13"), metrics = "users", dimensions = c("transactionId"), max = -1) #Your transaction ids rowa <- as.list(data$transactionId) #the other list of transaction ids rowb <- as.list(sfData$ti) #make them into characters rowa <- as.character(rowa) rowb <- as.character(rowb) #Only get the ones that doesn't match list1 <- setdiff(rowb, rowa) #Make a dataframe from only those who are missing df <- sfData[sfData$ti %in% list1, ]
This is a very short tutorial, it is not formatted very pretty, but it should get the trick done in terms of validating if anything should be missing in terms of transactions in Google Analytics. Please leave a comment should you need further elaboration on this progress!