Data Science and Gaming
The invention of the internet fundamentally changed so many aspects of our lives, but did you know it changed the way game developers are collecting our data? Unlike a simple high-score list on the video games of yesterdays arcade, now game devs were able to collect data on how player were using their systems and games as they were doing so.
As players began to start buying games on their console, these companies began storing credit card data. As motion sensors saw a rise in popularity, consoles began collecting data like weight and facial features. All of this data is taken to provide services, increase profits, and decrease customer churn rate. More specifically the WiiFit exercise game collected health data for exercise purposes and the Xbox Kinect measured the distance between facial features to recognize users.
These features were very exciting at the time, and the general population was widely unsure about what else this data could be used for. Many people had no idea that this data now allowed companies to see exactly who is using their products and how they can better market them.
“Ubisoft uses the customer data we have primarily for our internal marketing and demographic studies, which are designed to constantly improve products and services we provide and ensure they meet customers’ and players’ expectations,” — Stéphanie Perotti (The Star).
The Ubisoft privacy policy states it can collect, at any time, information on its customers’ gaming habits including:
- The unique identity of the gaming console
- Internet provider
- Dates and times spent playing Ubisoft games
- Game scores, metrics and statistics
- How much money is spent in-game
These are just some of the many data points that gamers create and funnel to these companies, and it isn't necessarily bad! Game developers use this data for a wide variety of functions that make gaming better for everyone.
Development
Data Science has become an increasingly pivotal part of the game development process. Today almost every game that is releases is a data collecting machine of sorts that records everything a player does from time spent in a game, what a player is doing, and how a player plays the game. This allows for development companies to see exactly what people enjoyed doing most about their games and adjust their next installments to reflect that data. No longer are companies guessing to see what players will like in the next game (Although that still adds to some of the magic in games), but now they are given “roadmaps” on what engaged player the most in a game.
Design
Gaming data along with a developer’s creativity mesh to create interactive and complex worlds ripe for exploring. The gaming analytics insights are used to obtain the specific knowledge of what the player wants, to predict where games can go wrong, why, and when. New game concepts, storylines, and mechanics are designed using the data gained previously.
Object Identification
Since the early days game developers have been in a race to deliver on the next big innovation to catapult the industry forward. Today this still remains true as we see huge companies like Microsoft and EA battle it out seeing who can wow the audience more at their yearly conventions. This year we saw Microsoft come in with one of their most ambitious projects yet. The title, Microsoft Flight Simulator 2020 (MFS), is the newest addition to their MFS line which dates back to 1982, but the ambitious with this years installment was to use Big Data, specifically Bing map data to allow players to fly to and from any place on the planet with almost perfect realism. This is a feat never taken on by a game developer, so who else but Microsoft to give it a go. The result is stunning realism that will captivate anyone as you take a relaxing flight over your hometown. However all this beauty comes at a cost.
The price for this stunningly high level of realism is data, and a lot of it. Microsoft Flight Simulator leverages Bing maps data, accessing over two petabytes of data from the cloud on demand. Microsoft teamed up with Blackshark.ai to develop a solution that uses Microsoft Azure cloud and Artificial Intelligence that analyzes map data and photogrammetry to generate photorealistic 3D models of buildings, tree, terrain, and so on. This is what allows the sim to depict most places on earth in photorealism. The game utilizes satellite imagery or fly by image scans as the basis for height and terrain texture data. MFS features multiple terabytes of texture and height map data.
Monetization
In theory, the more money a game makes, the better the company’s next product can be. With more money comes more resources, more talent, and more insight which should mean better games. Gaming companies use Data Science to increase their monetization by collecting user data about what you play, for how long, do you spend money on DLC, what DLC you buy, what other genres interest you from other games you play, etc in order to put the next thing you want to buy right in-front of your face so you know just what to buy. This is no different than Amazon showing you a list of recommended items for you to buy.
Companies can also take a more investigative approach and collect information from social media to see how people are reacting to their game. If people have concerns or praise will be a good indicator where/if they need to make fixes. This is seen more and more in modern gaming as games are never truly “finished” they are constantly being worked on and updated throughout the entire lifecycle.
Personalized Marketing
Personalized marketing is something everyone is familiar with maybe even if they are unaware what is happening. Personalized marketing is the act of marketing to each person individually based on what their data says they want to see. This is both good and bad. The good thing about this is that often times you see a recommendation for exactly what you want. This is bad because you may be pushed further and further down one rabbit hole and not organically experience new things as they come to you.
Game companies do this both in media and in their in game marketplaces as well. For example you may get a ad on Youtube to download Fortnite because you have been watching Fortnite videos or streams. Similarly in the Fortnite store they may push items to your storefront homepage that they have a good assumption you will be interested in.
Conclusion
The gaming industry has been growing exponentially there is no doubt about that. The number of active players seems to be increasing day after day, and with that so does the bank accounts of the companies pumping out these games.
The increase in quality among the Gaming industry is in part a result of the increased use of Data Science. Along with creating better games with top level visualization, graphics, and immersion from using Big Data, but game companies are also able to better market their products to the people who would enjoy them most. Data Science has become an integral part of the gaming industry, and it is exiting to see the magic that data and creativity can create together.
