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

Autor(en)
Sandra Boric, Christine Strauss
Abstrakt

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.

Organisation(en)
Institut für Marketing und International Business
Externe Organisation(en)
Karl-Franzens-Universität Graz
Seiten
479-504
DOI
https://doi.org/10.1007/978-3-030-95813-8_19
Publikationsdatum
2022
Peer-reviewed
Ja
ÖFOS 2012
502019 Marketing, 502007 E-Commerce, 509014 Spielforschung
ASJC Scopus Sachgebiete
Computer Science (miscellaneous), Control and Systems Engineering, Automotive Engineering, Social Sciences (miscellaneous), Economics, Econometrics and Finance (miscellaneous), Control and Optimization, Decision Sciences (miscellaneous)
Link zum Portal
https://ucris.univie.ac.at/portal/de/publications/systematic-retrieval-and-analysis-of-heterogenous-online-retail-platform-data-to-support-customer-targeting-in-gaming-business(9ae1c146-0d5e-4d2c-8f72-f65744b25bbe).html