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Transaction level attribution with Markov model



In the following use case, you will learn how to perform transaction level attribution using Markov model on your customer journey data.

Import libraries

library(ChannelAttributionPro)

Set the password

password="mypassword"

Load data

Data = read.csv("https://app.channelattribution.net/data/Data.csv",sep=";")
print(Data)

Perform transaction level attribution reading data from a data.frame

res=markov_model(Data=Data, var_path="path", var_conv="total_conversions", var_value="total_conversion_value",
var_null="total_null", cha_sep=">", password=password)
path_attribution=res$attribution
print(path_attribution)

Return non converting paths in the output data.frame

res=markov_model(Data=Data, var_path="path", var_conv="total_conversions", var_value="total_conversion_value",
var_null="total_null", cha_sep=">", flg_write_nulls=1, password=password)
path_attribution=res$attribution
print(path_attribution)

Return paths in the output data.frame

res=markov_model(Data=Data, var_path="path", var_conv="total_conversions", var_value="total_conversion_value",
var_null="total_null", cha_sep=">", flg_write_paths=1, password=password)
path_attribution=res$attribution
print(path_attribution)