Multi-Channel Attribution With R

Kevin Feasel

2017-06-01

R

Sergey Bryl walks through some of the difficulties of the multi-channel attribution solution he came up with before:

The main steps that we will review are the following:

  • splitting paths depending on purchases counts

  • replacing some channels/touch points

  • a unique channel/touchpoint case

  • consequent duplicated channels in the path and higher order Markov chains

  • paths that haven’t led to a conversion

  • customer journey duration

  • attributing revenue and costs comparisons

There’s a lot there, and I like the practical explanations of issues when dealing with a real business problem.

Related Posts

Spark And H2O

Avkash Chauhan shows how to use sparklyr and rsparkling to tie Spark together with the H2O library in R: In order to work with Spark H2O using rsparkling and sparklyr in R, you must first ensure that you have both sparklyr and rsparkling installed. Once you’ve done that, you can check out the working script, the […]

Read More

Power BI Supports Interactive R Visuals

David Smith reports on a great update to Power BI: The above chart was created with the plotly package, but you can also use htmlwidgets or any other R package that creates interactive graphics. The only restriction is that the output must be HTML, which can then be embedded into the Power BI dashboard or […]

Read More

Categories

June 2017
MTWTFSS
« May  
 1234
567891011
12131415161718
19202122232425
2627282930