LTV Forecast Modeling for the Free-to-play Game

Student: Sterkhov Sergey

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2017

This paper describes forecasting of LTV metrics for free-to-play game project. For this aim data from certain free-to-play game project was collected. However, for the purpose of privacy data has been noised. Firstly, articles about LTV prediction for projects in other fields are glimpsed. Secondly, the problem of input data is stated. Then, feature engineering stage and algorithm calculations are described. After this, results are compared with ones from the other model using single-purpose metrics. Subsequent to the results, proposed approach could be implemented into future projects for LTV forecasting.

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