Application of Developers’ and Users’ Dependent Factors in App Store Optimization

Application of Developers’ and Users’ Dependent Factors in App Store Optimization

app store optimization

Google Play

Apple App Store

mobile app store

ASO

This paper presents an application of developers' and users' dependent factors in the app store optimization. The application is based on two main fields: developers’ dependent factors and users’ dependent factors. Developers’ dependent factors are identified as: developer name, app name, subtitle, genre, short description, long description, content rating, system requirements, page url, last update, what’s new and price. Users’ dependent factors are identified as: download volume, average rating, rating volume and reviews. The proposed application in its final form is modelled after mining sample data from two leading app stores: Google Play and Apple App Store. Results from analyzing collected data show that developer dependent elements can be better optimized. Names and descriptions of mobile apps are not fully utilized. In Google Play there is one significant correlation between download volume and number of reviews, whereas in App Store there is no significant correlation between factors.

Strzelecki, Artur

International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 13 (2020); pp. 91-106

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2020-08-14

Copyright (c) 2020 Artur Strzelecki

application/pdf

eng

info:eu-repo/semantics/article

info:eu-repo/semantics/publishedVersion

Peer-reviewed Article