markov_model {ChannelAttribution}R Documentation

Markov model for the online attribution problem.

Description

Estimate a k-order Markov model from customer journey data.

Usage

markov_model(Data, var_path, var_conv, var_value=NULL, var_null=NULL, 
             order=1, nsim=NULL, max_step=NULL, out_more=FALSE, sep=">", 
             seed=NULL)

Arguments

Data

data.frame containing paths and conversions.

var_path

column name containing paths.

var_conv

column name containing total conversions.

var_value

column name containing total conversion value.

var_null

column name containing total paths that do not lead to conversions.

order

Markov Model order.

nsim

total simulations from transition matrix.

max_step

maximum number of steps for a single simulated path.

out_more

if TRUE returns the transition probabilities between channels and removal effects.

sep

separator between the channels.

seed

random seed. Giving to this parameter the same value over different runs guarantee that results will not vary.

Value

An object of class data.frame with the estimated number of conversions and the estimated conversion value attributed to each channel.

Author(s)

Davide Altomare (davide.altomare@gmail.com).

Examples


## Not run: 

library(ChannelAttribution)

data(PathData) 

markov_model(Data, "path", "total_conversions")
markov_model(Data, "path", "total_conversions", var_value="total_conversion_value")
markov_model(Data,"path","total_conversions", var_value="total_conversion_value", 
             var_null="total_null")
markov_model(Data, "path", "total_conversions", var_value="total_conversion_value", 
             var_null="total_null", out_more=TRUE)


## End(Not run)


[Package ChannelAttribution version 1.16 Index]