ggplot channelattribution.r

#visualize in ggplot
ggplot(R1, aes(channel_name, value, fill = variable)) +
  geom_bar(stat='identity', position='dodge') +
  ggtitle('TOTAL CONVERSIONS') + 
  theme(axis.title.x = element_text(vjust = -2)) +
  theme(axis.title.y = element_text(vjust = +2)) +
  theme(title = element_text(size = 16)) +
  theme(plot.title=element_text(size = 20)) +
  ylab("")

google analytics channelattribution.r

#install the packages
install.packages("ChannelAttribution")
install.packages("reshape")
install.packages("ggplot2")

#run libraries
library(ChannelAttribution)
library(reshape)
library(ggplot2)

Data <- read.csv("C:\\your sub folder\\markov chain test.csv",sep=",")
ChData <- as.data.frame(Data)
View(ChData)
head(ChData)
summary(ChData)

#regular models> first touch , last touch, linear
H <- heuristic_models(ChData, 'ï..path', 'total_conversions','total_conversion_value')

#markov model
M <- markov_model(ChData, 'ï..path', 'total_conversions', var_value='total_conversion_value', order = 1, var_null = 'total_null') 
R <- merge(H, M, by='channel_name') 
R1 <- R[, (colnames(R)%in%c('channel_name', 'first_touch_conversions', 'last_touch_conversions', 'linear_touch_conversions', 'total_conversion'))]
colnames(R1) <- c('channel_name', 'first_touch', 'last_touch', 'linear_touch', 'markov_model') 
R1 <- melt(R1, id='channel_name')

#visualize in ggplot
ggplot(R1, aes(channel_name, value, fill = variable)) +
  geom_bar(stat='identity', position='dodge') +
  ggtitle('TOTAL CONVERSIONS') + 
  theme(axis.title.x = element_text(vjust = -2)) +
  theme(axis.title.y = element_text(vjust = +2)) +
  theme(title = element_text(size = 16)) +
  theme(plot.title=element_text(size = 20)) +
  ylab("")

heuristic vs markov.r

#regular models> first touch , last touch, linear
H <- heuristic_models(ChData, 'ï..path', 'total_conversions','total_conversion_value')

#markov model
M <- markov_model(ChData, 'ï..path', 'total_conversions', var_value='total_conversion_value', order = 1, var_null = 'total_null')

load data for channel attribution.r

#install the packages
install.packages("ChannelAttribution")
install.packages("reshape")
install.packages("ggplot2")

#run libraries
library(ChannelAttribution)
library(reshape)
library(ggplot2)

Data <- read.csv("C:\\Your sub folder\\markov chain test.csv",sep=",")
ChData <- as.data.frame(Data)
View(ChData)
head(ChData)
summary(ChData)

merge models.r

R <- merge(H, M, by='channel_name') 
R1 <- R[, (colnames(R)%in%c('channel_name', 'first_touch_conversions', 'last_touch_conversions', 'linear_touch_conversions', 'total_conversion'))]
colnames(R1) <- c('channel_name', 'first_touch', 'last_touch', 'linear_touch', 'markov_model') 
R1 <- melt(R1, id='channel_name')