User retention is a keyword in the current mobile game industry as companies are trying their hardest to hook players into incorporating the game into their daily routines. Every time the player starts playing, it is a monetization oppor-tunity for the game. When players are happy with the game and like to spend time on it, they might spend money on it. Retention in technology and software use means the act of coming back to a product after the initial try. Luton, in his 2013 book Free-to-Play, Making Money From Games You Give Away, defines retention as the number of users retained over a given period of time. The defi-nition is good and is used in this study. Retention is a percentage-based number.
100% retention would that all users return to the product on a set amount of time and 0% is of course the opposite. N Day retention measures how many of the users come back on a particular day (Amplitude, 2018). For example, day one retention is measured when the user returns to the product on the next day. Day one retention can make or break a game. Developers and publishers are gathering massive amounts of data from every play session in most mobile games and early in the games production and lifecycle, retention is the most looked at numerical data. After all, mobile games lose most of the players after the initial install and test (Drachen, Lundquist, et al. 2016). This is true whether it is a premium or a free-to-play game. The decrease in retention is much more obvious in free-to-play games where the customer can install a game and after trying it, decide that’s it’s
not worth their time. In premium games, where the user pays upfront before the install, the risk of losing customers is much less problematic for the game pro-vider, because they already got the income from that user. For the players, pre-mium games are more of risk to get into, because of the price tag associated with them, so they often do more research on the subject prior to the purchase.
Fields (2014) point to how user retention is a way to keep the game alive for a long period of time. By keeping old players and using the revenue generated from them to acquire new players, the drop-off of users is not killing the game.
This is called the ARM funnel (acquisition, retention monetization). While much of the player base is changing often, having high retention is allowing the com-pany to support the game and get new users. The ARM funnel is presented in the figure 1.
Figure 1. The ARM Funnel (Fields 2014).
Day one retention means how many users return to the product after one day. A high number of first day returners is key on making a profitable game using a freemium model. In a freemium model, the game is designed around making the users pay small amounts of money through in-app-purchases (IAP) multiple times. The IAP is optional as the game is not truly free-to-play if it is mandatory.
Even the users who don’t turn in revenue from the IAPs are often targeted with ads that bring some value from those users. One estimation to monetization is that only 1 -3% of users are actually bringing in the revenue to the game through
in-app purchases. Very few players spend large quantities of money in them. To make this business model viable, game publishers and game studios need to hit a large number of downloads and the retention percentage needs to be high. (Cal-laghan, 2014, Using Game Analytics to Measure Student Engagement/Retention for Engineering Education). User acquisition is expensive and it’s getting more expensive every year, as more and more companies and studios are entering the market with their games. Gone are the days when mobile games were few and far between. The number of games released every month and even on a single day is staggering. Ever since Apple launched the first Iphone in 2007 and the App-store later in 2008, the market has flooded with new developers in hopes of becoming the next Angry Birds or Candy Crush Saga (Behrmann et al. 2011).
Currently the IOS store is getting over 500 new game releases every day (Pock-etgamer, 2018. App Store Metrics). Getting data from the android Google Play is a bit harder, the number of applications in the marketplace is rising steadily with over 3 500 000 total applications on December of 2017 (Statista, 2018, Number of available applications in the Google Play Store from December 2009 to December 2017). That number contains every application released on the platform, not just the games, but it gives a clue on how saturated the marketplace is.
The amount of research done for retention in mobile games is still lacking and the field of study is in its infancy. Although mobile games have been a big new field. Majority of the previous works only acknowledge retention as an im-portant aspect of mobile games monetization model, as is with all freemium products. The majority of the work is done around the monetization, in-app-pur-chases (IAPs) and how to predict the user making purchasing decisions. Research has been done on user retention, but sadly it is lacking a practical application.
Drachen et al. created a model in 2016 for predicting customer retention using heuristics and machine learning but the dataset they used, and the heuristics don’t take notice of different game mechanics and gameplay elements and only focus on metrics such as playtime length and total sessions etc. The predictive nature of that study fails to be much of use for game creators and this study.
At least one major publication of retention study in videogames is the 2011, Modeling Player Retention in Madden NFL 11 by Weber, John, Mateas and Jhala.
It focuses on studying what gameplay loops keep getting players to come back to the game on a daily basis and even on a yearly standard. This study is focused more on how retention influences future work and the product in its current state.
This is a common trait of many studies on retention. For this reason, a throughout study on nature of playing is needed before we can study how players are being retained by games.