Systematic Retrieval and Analysis of Heterogenous Online Retail Platform Data to Support Customer Targeting in Gaming Business
- Author(s)
- Sandra Boric, Christine Strauss
- 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.
- Organisation(s)
- Department of Marketing and International Business
- External organisation(s)
- Karl-Franzens-Universität Graz
- Pages
- 479-504
- DOI
- https://doi.org/10.1007/978-3-030-95813-8_19
- Publication date
- 2022
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 502019 Marketing, 502007 E-commerce, 509014 Game research
- ASJC Scopus subject areas
- Computer Science (miscellaneous), Control and Systems Engineering, Automotive Engineering, Social Sciences (miscellaneous), Economics, Econometrics and Finance (miscellaneous), Control and Optimization, Decision Sciences (miscellaneous)
- Portal url
- https://ucrisportal.univie.ac.at/en/publications/systematic-retrieval-and-analysis-of-heterogenous-online-retail-platform-data-to-support-customer-targeting-in-gaming-business(9ae1c146-0d5e-4d2c-8f72-f65744b25bbe).html