TY - GEN
T1 - To be or not to be... social
T2 - 2018 Australasian Computer Science Week Multiconference, ACSW 2018
AU - Drachen, Anders
AU - Pastor, Mari
AU - Liu, Aron
AU - Fontaine, Dylan Jack
AU - Chang, Yuan
AU - Runge, Julian
AU - Sifa, Rafet
AU - Klabjan, Diego
N1 - Publisher Copyright:
© 2018 ACM.
PY - 2018/1/29
Y1 - 2018/1/29
N2 - Mobile games make up the largest segment of the games industry, in terms of revenue as well as players. Hundreds of thousands of games are available with most being free to download and play. In freemium games, revenue is predominantly generated by users making in-game purchases. As only a small fraction of users make purchases, predicting these users and their Customer Lifetime Value are key challenges in Game Analytics and currently barely explored in academic research. Furthermore, while social factors have been shown to be essential for retention in games in general, the impact on retention and monetization in mobile games is unexplored. In this paper, the problem of defining social features in freemium casual mobile games is addressed through a case study with over 200,000 players. .e study evaluates the in.uence of specific types of social interactions typical of casual mobile games, on predictions of premium users and Customer Lifetime Value by applying classifiers and regression models respectively. Results indicate that social activity does not correlate with the tendency to become a premium user, but that social activity increases over time in a cohort.
AB - Mobile games make up the largest segment of the games industry, in terms of revenue as well as players. Hundreds of thousands of games are available with most being free to download and play. In freemium games, revenue is predominantly generated by users making in-game purchases. As only a small fraction of users make purchases, predicting these users and their Customer Lifetime Value are key challenges in Game Analytics and currently barely explored in academic research. Furthermore, while social factors have been shown to be essential for retention in games in general, the impact on retention and monetization in mobile games is unexplored. In this paper, the problem of defining social features in freemium casual mobile games is addressed through a case study with over 200,000 players. .e study evaluates the in.uence of specific types of social interactions typical of casual mobile games, on predictions of premium users and Customer Lifetime Value by applying classifiers and regression models respectively. Results indicate that social activity does not correlate with the tendency to become a premium user, but that social activity increases over time in a cohort.
KW - Behavioral Prediction
KW - Computer Games
KW - Customer Lifetime Value
KW - Freemium
KW - Game Analytics
UR - http://www.scopus.com/inward/record.url?scp=85044777901&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044777901&partnerID=8YFLogxK
U2 - 10.1145/3167918.3167925
DO - 10.1145/3167918.3167925
M3 - Conference contribution
AN - SCOPUS:85044777901
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2018
PB - Association for Computing Machinery
Y2 - 29 January 2018 through 2 February 2018
ER -