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Churn Prediction for Game Industry Based on Cohort Classification Ensemble

Author

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  • Tsymbalov, Evgenii

Abstract

In this paper, we present a cohort-based classification approach to the churn prediction for social on-line games. The original metric is proposed and tested on real data showing a good increase in revenue by churn preventing. The core of the approach contains such components as tree-based ensemble classifiers and threshold optimization by decision boundary.

Suggested Citation

  • Tsymbalov, Evgenii, 2016. "Churn Prediction for Game Industry Based on Cohort Classification Ensemble," MPRA Paper 82871, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:82871
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    File URL: https://mpra.ub.uni-muenchen.de/82871/1/paper8.pdf
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    Cited by:

    1. Osipov, Vasiliy & Zhukova, Nataly & Miloserdov, Dmitriy, 2019. "Neural Network Associative Forecasting of Demand for Goods," MPRA Paper 97314, University Library of Munich, Germany, revised 23 Sep 2019.

    More about this item

    Keywords

    Churn prediction; ensemble classification; cohort-based prediction; on-line games; game analytics;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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