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Systematic Retrieval and Analysis of Heterogenous Online Retail Platform Data to Support Customer Targeting in Gaming Business

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Developments in Information & Knowledge Management for Business Applications

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 420))

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Abstract

This study demonstrates how heterogenous data can be retrieved from global yet regionally tailored online retail platforms. A systematic data retrieval approach is suggested to obtain data from regional Amazon and Nintendo websites. The data retrieval uses a 3 × 3 criteria setting: Three attributes (genre, age rating, player-count), three forms of analysis (distribution, reception, price), and three countries (Germany, United States, Japan). A streamlined choice of entries on the chosen online retail platforms is suggested. We determine adequate criteria that allow for data comparisons between different regions. This study’s systematic approach provides first-step solutions to gather, interpret, and manage information derived from online retail platforms to increase its business usage and value. The analysis of rating, pricing, and age rating similarities and differences in various countries is of value to game research and game developer studios. It can provide a basis to develop successful strategies for customer targeting in different regions.

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Authors and Affiliations

  1. University of Graz, Elisabethstraße 50 b/I, 8010, Graz, Austria

    Sandra Boric

  2. University of Vienna, Oskar Morgenstern Platz 1, 1090, Vienna, Austria

    Christine Strauss

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  1. Sandra Boric
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  1. Department of Information Systems, Faculty of Management, Comenius University, Bratislava, Slovakia

    Natalia Kryvinska

  2. Department of Information Systems, Faculty of Management, Comenius University, Bratislava, Slovakia

    Michal Greguš

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Boric, S., Strauss, C. (2022). Systematic Retrieval and Analysis of Heterogenous Online Retail Platform Data to Support Customer Targeting in Gaming Business. In: Kryvinska, N., Greguš, M. (eds) Developments in Information & Knowledge Management for Business Applications. Studies in Systems, Decision and Control, vol 420. Springer, Cham. https://doi.org/10.1007/978-3-030-95813-8_19

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