How Data Science Transformed Gaming Industry

HOW DATA SCIENCE TRANSFORMED THE GAMING INDUSTRY

By Wahyu Kwan | December 28, 2020

Over the past few years, the number of players in the gaming industry has skyrocketed from a total of 1.99 billion gamers across the globe in 2015 to 2.7 billion gamers in 2020.

With the growing numbers, there is no doubt that Data Science has become the number 1 tool for gaming organizations to keep up with the others. Most organizations collect your gaming data such as your playing time, quitting point, rank/scores, etc. Some even took it to the next step and have implemented an Artificial Intelligence bot to play against you in a complex multiplayer game like Dota 2.

What used to be a human-designed game for you has now transformed into a data-driven designed game that provides an exceptional gaming experience. Hence, opening up many opportunities for game companies to apply Data Science use cases for optimization and improvements. In today’s blog post, we’re going to cover how Data Science is playing a significant role in the gaming industry.

GAME DEVELOPMENT

When it comes to developing a well-designed game that keeps you hooked, tons of data are required for Data Experts to analyze and identify optimization points. In fact, this has been one of the main reasons why video game companies conduct Focus Groups, Close Beta Tests, and Open Beta Tests. How are the players interacting with the game? Where are the players moving to? What kinds of characters are they using and why? These types of feedback from the community will never end and it requires multiple Data Scientists to collect, analyze, and turn it into a useful insight for the company, such as new content and features to add.

step-by-step process from how data science transform gaming industry

VISUAL EFFECTS & GRAPHICS

Nowadays, it’s equally important to have games that are visually appealing and provide an overall good gaming experience. If you’ve looked up any game reviews on YouTube, most videos are going to cover the visual effects & graphics aspect of the game at some point. In order to come up with visually appealing games, Data Scientists use motion capture, real-time rendering, and photogrammetric that enables them to create in-game characters with facial expressions, emotions, and movements that look natural to you. Take Nvidia as an example. Nvidia, the giant graphic card company, optimizes Deep Learning Super Sampling (DLSS) which effectively allows the GPU and PC to render games at a higher resolution than what the monitor can handle.

GAME MONETIZATION

Developing a well-designed game that keeps you engaged takes up a lot of company resources. Thus, game publishers’ main goal is to make a profit off of their games. There exist a few business models in the gaming industry that helps publishers monetize games:

Physical Store – where you buy a physical copy of the game in retail stores (e.g. Gamestop, GameMartz).

Digital Store – where you make a one time purchase from an online store or directly on your device (e.g. App Store/Google Play, Steam, Blizzard).

Subscription – where a game requires you to make a recurring payment to play the game, usually monthly based (e.g. Final Fantasy XIV, World of Warcraft).

Free to play – where the game is free for you to play, but the company provides in-app purchases like character skins that give you visual effects or limited-time event only character (e.g. League of Legends, Dota 2, Genshin Impact).

Data-Driven Advertisements – An indirect form of monetization from 1 business to another.

With the help of Big Data analytics tools, gaming companies can now predict your behavior towards the game and optimize their games to keep you engaged and interested. Steam, a video game digital distribution service by Valve, has been using this technology since day 1. If you login into your Steam account, you will see many game recommendations that you might be interested in. What’s behind the recommendation system? Data Science.

DETECTING CHEATERS/HACKERS

If you’ve played an online game before, I’m almost 100% sure that you’ve at least encountered a cheater or hacker at least once in your life, be it in a massively multiplayer game or a small game on the internet. I’ve personally experienced it and I know that it sucks to be played against them. It just feels unfair, doesn’t it? Well luckily enough for both of us, gaming companies nowadays have Machine Learning in their hands to detect even the slightest malicious activity. It has been proven by the community that the number of cheaters and the fast-growing technology within the gaming industry is heavily correlated. Big companies like Riot Games that have the resources have been exceptionally well in detecting cheats in their games, giving them a competitive edge over the others.

illustration of laptop, console, and headphone, connecting gamers online

SOCIAL & CUSTOMER ANALYSIS

Streaming video games are starting to rise in popularity especially with a lot of people staying at home during the pandemic. Without realizing it, you might’ve stopped by someone’s stream or YouTube channel and join their community within multiple platforms. The community usually interacts actively and is separated based on mutual interests and goals towards the game. This is critical for gaming publishers as it allows them to target different customers, understand your perception of the game, and develop the right strategies for you. The analysis result also helps them understand your behaviors, feedback, and loyalty towards the brand.

CONCLUSION

The gaming industry is getting more active users every minute of the day and the numbers are growing exponentially. With it, the backend infrastructure gets even more complex, providing gamers like you with top-notch graphic design elements and visual effects which results in high levels of satisfaction. Moreover, Data Science has become the core of all games, and thanks to Data Science, you can now be a part of an extraordinary gaming community. Now if you find this blog post helpful, don’t forget to share it with your fellow gamer friends and as always, work hard, play hard!

Yuk belajar data science di Algoritma Data Science Education Center! Kamu bisa ikut berbagai kelas data science untuk pemula, salah satunya di program Academy kami.

PELAJARI LEBIH LANJUT

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Over the past few years, the number of players in the gaming industry has skyrocketed from a total of 1.99 billion gamers across the globe in 2015 to 2.7 billion gamers in 2020.

With the growing numbers, there is no doubt that Data Science has become the number 1 tool for gaming organizations to keep up with the others. Most organizations collect your gaming data such as your playing time, quitting point, rank/scores, etc. Some even took it to the next step and have implemented an Artificial Intelligence bot to play against you in a complex multiplayer game like Dota 2.

What used to be a human-designed game for you has now transformed into a data-driven designed game that provides an exceptional gaming experience. Hence, opening up many opportunities for game companies to apply Data Science use cases for optimization and improvements. In today’s blog post, we’re going to cover how Data Science is playing a significant role in the gaming industry.

GAME DEVELOPMENT

When it comes to developing a well-designed game that keeps you hooked, tons of data are required for Data Experts to analyze and identify optimization points. In fact, this has been one of the main reasons why video game companies conduct Focus Groups, Close Beta Tests, and Open Beta Tests. How are the players interacting with the game? Where are the players moving to? What kinds of characters are they using and why? These types of feedback from the community will never end and it requires multiple Data Scientists to collect, analyze, and turn it into a useful insight for the company, such as new content and features to add.

VISUAL EFFECTS & GRAPHICS

Nowadays, it’s equally important to have games that are visually appealing and provide an overall good gaming experience. If you’ve looked up any game reviews on YouTube, most videos are going to cover the visual effects & graphics aspect of the game at some point. In order to come up with visually appealing games, Data Scientists use motion capture, real-time rendering, and photogrammetric that enables them to create in-game characters with facial expressions, emotions, and movements that look natural to you. Take Nvidia as an example. Nvidia, the giant graphic card company, optimizes Deep Learning Super Sampling (DLSS) which effectively allows the GPU and PC to render games at a higher resolution than what the monitor can handle.

GAME MONETIZATION

Developing a well-designed game that keeps you engaged takes up a lot of company resources. Thus, game publishers’ main goal is to make a profit off of their games. There exist a few business models in the gaming industry that helps publishers monetize games:

Physical Store – where you buy a physical copy of the game in retail stores (e.g. Gamestop, GameMartz).

Digital Store – where you make a one time purchase from an online store or directly on your device (e.g. App Store/Google Play, Steam, Blizzard).

Subscription – where a game requires you to make a recurring payment to play the game, usually monthly based (e.g. Final Fantasy XIV, World of Warcraft).

Free to play – where the game is free for you to play, but the company provides in-app purchases like character skins that give you visual effects or limited-time event only character (e.g. League of Legends, Dota 2, Genshin Impact).

Data-Driven Advertisements – An indirect form of monetization from 1 business to another.

With the help of Big Data analytics tools, gaming companies can now predict your behavior towards the game and optimize their games to keep you engaged and interested. Steam, a video game digital distribution service by Valve, has been using this technology since day 1. If you login into your Steam account, you will see many game recommendations that you might be interested in. What’s behind the recommendation system? Data Science.

DETECTING CHEATERS/HACKERS

If you’ve played an online game before, I’m almost 100% sure that you’ve at least encountered a cheater or hacker at least once in your life, be it in a massively multiplayer game or a small game on the internet. I’ve personally experienced it and I know that it sucks to be played against them. It just feels unfair, doesn’t it? Well luckily enough for both of us, gaming companies nowadays have Machine Learning in their hands to detect even the slightest malicious activity. It has been proven by the community that the number of cheaters and the fast-growing technology within the gaming industry is heavily correlated. Big companies like Riot Games that have the resources have been exceptionally well in detecting cheats in their games, giving them a competitive edge over the others.

SOCIAL & CUSTOMER ANALYSIS

Streaming video games are starting to rise in popularity especially with a lot of people staying at home during the pandemic. Without realizing it, you might’ve stopped by someone’s stream or YouTube channel and join their community within multiple platforms. The community usually interacts actively and is separated based on mutual interests and goals towards the game. This is critical for gaming publishers as it allows them to target different customers, understand your perception of the game, and develop the right strategies for you. The analysis result also helps them understand your behaviors, feedback, and loyalty towards the brand.

CONCLUSION

The gaming industry is getting more active users every minute of the day and the numbers are growing exponentially. With it, the backend infrastructure gets even more complex, providing gamers like you with top-notch graphic design elements and visual effects which results in high levels of satisfaction. Moreover, Data Science has become the core of all games, and thanks to Data Science, you can now be a part of an extraordinary gaming community. Now if you find this blog post helpful, don’t forget to share it with your fellow gamer friends and as always, work hard, play hard!

Yuk belajar data science di Algoritma Data Science Education Center! Kamu bisa ikut berbagai kelas data science untuk pemula, salah satunya di program Academy kami.

PELAJARI LEBIH LANJUT