20.500.12556/RUL-124377 Extended RFM logit model for churn prediction in the mobile gaming market As markets are becoming increasingly saturated, many businesses are shifting their focus to customer retention. In their need to understand and predict future customer behavior, businesses across sectors are adopting data-driven business intelligence to deal with churn prediction. A good example of this approach to retention management is the mobile game industry. This business sector usually relies on a considerable amount of behavioral telemetry data that allows them to understand how users interact with games. This high-resolution information enables game companies to develop and adopt accurate models for detecting customers with a high attrition propensity. This paper focuses on building a churn prediction model for the mobile gaming market by utilizing logistic regression analysis in the extended recency, frequency and monetary (RFM) framework. The model relies on a large set of raw telemetry data that was transformed into interpretable game-independent features. Robust statistical measures and dominance analysis were applied in order to assess feature importance. Established features are used to develop a logistic model for churn prediction and to classify potential churners in a population of users, regardless of their lifetime. operations research mobile telephony games models operacijsko raziskovanje mobilna telefonija igre modeli true false false Angleški jezik Slovenski jezik Članek v reviji 2021-01-19 14:45:56 2021-01-19 14:52:33 2022-09-04 03:59:07 0000-00-00 00:00:00 2020 0 0 Str. 249-261 iss 2 Vol. 11 2020 0000-00-00 Zaloznikova NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 658.5(045) 1848-0225 10.17535/crorr.2020.0020 43848707 10670108 RAZ_Perisic_Ana_2020.pdf RAZ_Perisic_Ana_2020.pdf 1 95C21CA57FA1E223E4986BB533ECA1A8 465689e849d5d6216605e7ca4144cc4817877b0594e817ba63bf8db6e833ed4e 89d56cda-a1bb-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=139819 https://hrcak.srce.hr/ojs/index.php/crorr/article/view/12125 1 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=139820 Ekonomska fakulteta 0 0 0