Big data and the video game industry have a long and storied history, owing to the fact that video games have been a primary factor in pushing PC technology over the years. But when we say “big data”, we’re not really talking about the size of video games, though that plays a role somewhere in the line.
What we mean by “big data” is the research performed on, and statistics collected from, the video game industry. Big data isn’t anything new, its just a modern term for storing information for later analysis, and in many cases, tailoring a product or experience to user trends gathered from the data.
The thing that separates “big data” from regular “data analytics” is the amount of data being analyzed. Big data really is that – immense amounts of data that is impossible to store on a single computer, in fact it probably requires a data center. We’re talking about data that is collected from millions of users across a platform, rather than say, your typical WordPress analytics panel.
So how exactly is big data used? Facebook, for example, gathers our data every day, including browser cookies from other websites we’ve visited – thus, Facebook is able to show “relevant ads” that are based on our personal data, e.g. things we’ve searched for across the internet. So big data is highly desirable for companies that rely on ad-based revenue, and data trading does happen between companies.
The above example isn’t exactly what happens in the video game industry, but its similar. Big data in the video game industry doesn’t really look at personalized big data – rather, big data gets measured and compared as a whole sum of an entire player-base. Usually.
Consider these facts as an example of the point we’re making:
● More than 2 billion gamers = 50 Tb of data / day.
● AAA multiplayer titles = about 1Tb of data / day from in-game telemetry.
● Social games = 150Gb of data / day.
● In a typical month, EA hosts about 2.5 billion game sessions, representing about 50 billion minutes of gameplay
By utilizing big data, the video game industry is able to tailor the product to player trends, such as:
● The number of players who are quitting the game at a certain stage.
● How many players are skipping the tutorial intro.
● What stage of gameplay players are more likely to make IAPs (in-app purchases).
● How often and for how long players check their farms or bases in a “consistent world” type of game (Farmville, Clash of Clans, etc.).
Thus, big data in the video game industry isn’t really used to tailor the gaming experience to any individual person, as social networking websites do with relevant advertisements – rather, the video game industry uses big data to refine gameplay for the entire player-base.
That’s not to say that social media can’t play a role here. If you connect your Facebook account to your game console, then you could start seeing relevant ads for video games that are similar to whatever you’re playing the most on your Xbox, or in your browser. For example if you play a lot of Run 2, you might be recommended to try the Jungle Run Temple.
Mobile games are big data’s best friend especially. This is because our mobile devices contain practically our entire personalities – everything we search for, all of our social media friends, all the music files we listen to, and all the apps we have installed. By tapping into these simple statistics (most of which are covered under app permissions you agree to when installing a new app, or connect a social media account to your game profile), ad networks that are bundled into mobile games can learn a lot about your user habits.
As mentioned earlier, big data in gaming isn’t used only for ad targeting (though that’s certainly a major factor), but for game developers to tweak gameplay to their audience’s habits. Electronic Arts notably used this around 2012 with popular first-person shooter Battlefield 3. By tracking each player’s “digital footprint” through gameplay (and remember, we’re talking about millions of players), EA was able to analyze massive amounts of data, such as how often players move through particular areas of a map.
The data was also analyzed for future considerations, such as match-making. In a presentation, Rajat Taneja, the CTO for EA at that time, spoke on how big data could be analyzed for matching up players of similar playstyles in Battlefield 3.
Big data analysis isn’t limited to just AAA titles and huge studios, however. It’s also used in browser-based gaming, such as online casinos, or even HTML5 games. Online casinos can use big data to decide which are their most popular games, and which games to display on their front pages. They can also predict pop-culture trends, such as when slots site Spin Genie offered a Game of Thrones-inspired slot game.
Big data and video games could create together an excellent research instrument of human learn capabilities. For example, let’s take the World’s Hardest Game and analyze users’ reactions, decision making, behaviours, errors - everything that plays part in mastering gaming skills. Recent DeepMind’s agent experiment on AI-bots is a nice example of the ability to collect and process such information. Game developers also could use such data to create more engaging and challenging games.