Game analytics has been used in game development and game research. However, less work focus on the game publishing side, especially on the new version update evaluation. This paper shows how game analytics can be used to guide game version updates. We innovatively view mobile game publishing as maintaining a fish tank and use our Fish Tank Model (FTM) to evaluate how game version updates improve players’ activation and game revenue. First, we define some key metrics for evaluating mobile game performance based on FTM. Second, we introduce a real game project to develop and apply FTM to the new version update. Third, based on analyzing the changes before and after the game version update, we provide suggestions on how to improve the new version. Finally, we summarize how to use our data-driven model to guide the mobile game new version update evaluation and continue to improve the game content.


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    Titel :

    A data-driven model for mobile game new version update evaluation


    Beteiligte:
    Su, Yanhui (Autor:in) / Backlund, Per (Autor:in) / Engström, Henrik (Autor:in)

    Erscheinungsdatum :

    2020-01-01


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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