Mobile gaming continues to be big business for both large and smaller game developers, with reports suggesting that the industry could be worth $76.7B in IAP and upwards of $65bn in ads by the end of 2020. Mobile apps and games are growing at 20% a year in revenue according to App Annie, with further predictions that users will collectively spend around 674 billion hours on mobile devices this year. As competition for screen time increases, developers are increasingly looking to in-game personalisation as a method for boosting retention.
The link between in-game personalisation, high retention and ARPU
There is often a very fine line between interest and boredom, so keeping users engaged for longer is a key marker in determining the success or failure of any mobile game. Each game appeals to certain segments of players, some of which can be rather niche. Personalisation is a way of increasing the appeal of a game to a broader audience by tailoring core in-game elements to their preferences.
Personalisation for core, mid-core and casual games
Personalisation in game play can take on a number of forms. More complicated core and mid-core games for example could have their personalisation focus on character aesthetics, such as hair colour or clothing. These types of games could also look into developing the gameplay so that users can take the story in different directions depending entirely on what they want to get out of the game. This is most often delivered via multi-pathway options where users can select from a series of predetermined routes, which in turn will create a unique progression throughout the game.
On the more casual side of the gaming market, where titles can enjoy millions of players engaging with, and providing usage data to the game, we’re starting to see exciting applications of machine learning techniques to better engage users at an individual level but at scale. Games can automatically ‘learn’ the user’s preferences, behaviour and gaming style and adapt the game accordingly. This could include varying the difficulty of levels depending on the user’s ability or serving monetisation opportunities that users respond well to, both improving retention rates and increasing ARPU. We are already seeing machine learning playing a significant part in game development, much in the same way as Spotify, Netflix and Amazon seek to learn behaviour patterns and use the data to deliver a better experience to their users.
Personalisation is profitability
Quite simply put, a well thought out personalisation strategy can be the difference between your game being profitable or not. By tailoring the user experience to keep players immersed in the game for longer and serving them the right ads, you can increase the delta between your ARPU and your CPI. When a game requires a user to invest time, creativity, imagination and energy into creating a character, progressing through a series of levels, or following through a storyline, the users are much more connected with the journey and are more likely to continue deeper into the game.
Personalisation is also typically needed to help attract the top spenders, our much lauded ‘whales’. These users typically generate up to 50% of the title’s revenue despite only making up around 1%-2% of total players. They can be connected for up to 16 hours a day and can spend up to $1,000 a day making in-app purchases.
Getting started
The first step in moving towards a more personalised gaming experience is understanding the outcomes and experiences that your target audience is likely to be looking for in a game. In the study ‘Towards a Trait Model of Video Game Preferences’, a team of multidisciplinary researchers at the University of Waterloo Games Institute identified three basic game player traits that can be utilised to make games more personalised and help keep gamers engaged and motivated. These top line traits included the level of preference for action, the aesthetic look and feel of the game, and degree of goal orientation. In addition, a range of player archetypes were identified, which included seeker, survivor, daredevil, mastermind, conqueror, socializer, and achiever. These profiles, alongside other factors such as age, gender and location all help to shape the development of the game so that it focuses on what the user most wants to experience whilst immersed in the game.
Gaining access to the critical user data needed to help guide personalisation strategies is now easier than ever thanks to solutions such as Coda’s SDK where collected data from in-game events is sent to the Coda Platform, with always-on machine learning helping to find the best parameters for future A/B testing. For example, Coda’s algorithms will analyse data from in-game events to suggest the best timing for interstitial ads, but ultimately is focused on improving the user experience, boosting engagement and enhancing monetisation in the long run.
Taking mobile gaming to new heights
What is clear is that data-driven personalisation is already transforming the gaming world so that it is no longer simply about a single gaming experience, but many different ones which are all shaped to meet the specific needs and interests of individual players. Embracing and building upon the in-game personalisation opportunities that large swathes of data and machine learning create is key to game survival, given that by 2021, mobile gaming is predicted to make up around 60% of the global gaming market. Game developers who can embed personalisation into the very DNA of their mobile games will be the ones who are best positioned for future success.
