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Attribution of Customers’ Actions Based on Machine Learning Approach

Author

Listed:
  • Kadyrov, Timur
  • Ignatov, Dmitry I.

Abstract

A multichannel attribution model based on gradient boost-ing over trees is proposed, which was compared with the state of theart models: bagged logistic regression, Markov chains approach, shapelyvalue. Experiments on digital advertising datasets showed that the pro-posed model is better than the solutions considered by ROC AUC metric.In addition, the problem of probability prediction of conversion by theconsumer using the ensemble of the analyzed algorithms was solved,the meta-features obtained were enriched with consumers and offlineactivities of the advertising campaign data.

Suggested Citation

  • Kadyrov, Timur & Ignatov, Dmitry I., 2019. "Attribution of Customers’ Actions Based on Machine Learning Approach," MPRA Paper 97312, University Library of Munich, Germany, revised 23 Sep 2019.
    • Handle: RePEc:pra:mprapa:97312
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    More about this item

    Keywords

    Multi-touch attribution; Gradient boosting; Digital advertising; Data-driven marketing;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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