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 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: | 2.2.4 |
| Imports: | Rcpp |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | curl,jsonlite |
| Published: | 2025-11-19 |
| DOI: | 10.32614/CRAN.package.ChannelAttribution |
| Author: | Davide Altomare [cre, aut], David Loris [aut] |
| Maintainer: | Davide Altomare <info at channelattribution.io> |
| License: | GPL-3 | fileLICENSE |
| Copyright: | see fileCOPYRIGHTS |
| URL: | https://channelattribution.io |
| NeedsCompilation: | yes |
| CRAN checks: | ChannelAttribution results |
| Reference manual: | ChannelAttribution.html ,ChannelAttribution.pdf |
| Package source: | ChannelAttribution_2.2.4.tar.gz |
| Windows binaries: | r-devel:ChannelAttribution_2.2.4.zip, r-release:ChannelAttribution_2.2.4.zip, r-oldrel:ChannelAttribution_2.2.4.zip |
| macOS binaries: | r-release (arm64):ChannelAttribution_2.2.4.tgz, r-oldrel (arm64):ChannelAttribution_2.2.4.tgz, r-release (x86_64):ChannelAttribution_2.2.4.tgz, r-oldrel (x86_64):ChannelAttribution_2.2.4.tgz |
| Old sources: | ChannelAttribution archive |
| Reverse imports: | ChannelAttributionApp |
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