ChannelAttribution: Markov Model for the Online Multi-Channel Attribution Problem

Advertisers use a variety of online marketing channels to reach consumers and they want to know the degree each channel contributes to their marketing success. This is called the online multi-channel attribution problem. This package contains a probabilistic algorithm for the attribution problem. The model uses a k-order Markov representation to identify structural correlations in the customer journey data. The package also contains three heuristic algorithms (first-touch, last-touch and linear-touch approach) for the same problem. The algorithms are implemented in C++.

Version: 1.13
Imports: Rcpp (≥ 0.11.4)
LinkingTo: Rcpp, RcppArmadillo
Published: 2018-06-11
Author: Davide Altomare, David Loris
Maintainer: Davide Altomare <davide.altomare at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.slideshare.net/adavide1982/markov-model-for-the-multichannel-attribution-problem http://www.lunametrics.com/blog/2016/06/30/marketing-channel-attribution-markov-models-r/ http://analyzecore.com/2016/08/03/attribution-model-r-part-1/
NeedsCompilation: yes
CRAN checks: ChannelAttribution results

Downloads:

Reference manual: ChannelAttribution.pdf
Package source: ChannelAttribution_1.13.tar.gz
Windows binaries: r-devel: ChannelAttribution_1.13.zip, r-release: ChannelAttribution_1.13.zip, r-oldrel: ChannelAttribution_1.13.zip
OS X binaries: r-release: ChannelAttribution_1.13.tgz, r-oldrel: ChannelAttribution_1.12.tgz
Old sources: ChannelAttribution archive

Reverse dependencies:

Reverse imports: ChannelAttributionApp

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