How Data Science Impacting Online Gaming Industry

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The gaming industry is booming! Developer companies are in a red ocean competition and not leaving a single stone unturned. Now, the most attraction for gaming companies is data science. As the Internet experts used to say, data is a gold mine. A lot many companies are relying on data science to develop new tools and improve their services. The gaming industry is also not left behind and using data science not only to develop more games but also to improve the services and features of their previous games.

Data analytics has been found to be more important for the online gaming industry due to the vast amount of data that is being collected, especially in those games that are being integrated with social networks like Facebook etc. The data that is being collected and analyzed by the data scientists includes the following.

  • Age and gender of players
  • Peak hours of activity
  • Gaming techniques by pro players
  • Obstacles in services
  • Missions of less and more interest

…. and a lot more. The following are the 6 key areas that are being developed and improved by the gaming industry using data science.

Fraud Detection

With Machine Learning (ML) and Artificial Intelligence (AI), fraud detection has become much easier and doesn’t involve much of the human interaction now. Algorithms record the behavior of the players, learn itself and make the automated decision in response to any fraudulent activity during the game.

For instance, After PUBG mobile was released, users started to play it on the computer as well using different simulators. Because the computer users were using peripheral devices like mouse and keyword. It was a bit easier for them to beat the mobile device players. PUBG introduced the algorithm that was able to detect that behavior and would ban the player from that specific server that was for the mobile players.

Improved Personalized Marketing

Game developers have tons of big data collection tools that help them find detailed information about trends, players, competitors, and their games. With this information, the companies can personalize payments to loyal players or make tailored promotions.

For instance, Online Casinos in Finland reviewed at Casinorella Finland can give new players up to £300 in bonuses on their first deposit. And if a player deposits money for the second time, they receive an extra bonus as a reward.

Personalized marketing is the integration of data analytics to train the machine learning algorithms to lure the players in to buying the stuff in-game or clicking on the ads. The fact is that, using data science we create a dystopia to make click on the ads. Relevant ads are on to the next level now and seem like highly targeted due to being data-driven.

Apart from that, personalized marketing helps gaming companies do not only depend on the data obtained during gameplay but also from the data companies as well as social media.

Customer Analysis

The best business model that attracts the companies these days is the subscription-based model. It helps earn the most and sustainable source of earning. Post-sale analysis is the most important thing when it comes to marketing. Tech companies with the most profit are those which have returning users and subscribers. Companies are now analyzing customer data to draw the probabilities of them buying more services inside the game or the next game company is about to launch.

For instance, Call of Duty Mobile was not a random decision by the Activision. Or this is not just like that they wanted to compete for the best mobile game against PUBG (True, up to some extent). But they analyzed the feedbacks and requests by their players or customers to launch a version of the game on the mobile platform and yes they did it. Now, let’s see how this turns out to be. There is mixed feedback so far about the game.


No one develops the game just out of interest. Market growth for the gaming industry this year $1.8 Billion USD and it is growing exponentially. Many more companies are joining in to make their part of the profit. Now the correct monetization techniques are necessary. Among the best models that are best used for monetization are Pay-to-Play, Freemium, and Ad-supported.

Using the data obtained during the game plays, machine learning algorithms decide the best monetization strategy for the game. During the game development, using data analytics, developers can make informed decisions about which monetization model will work best with a particular type of game.


Designing a good game is very important to assure the interest of the player in the game. With every day that passes, new technologies are being introduced for designing the animations and visual effects that must please a vast range of players. The designer now uses data science to design everything in the game.

Because it’s not just about the crazy graphics. In a game, the behavioral response is more important than anything else.  To study the behavior of players towards a specific object, researchers are designing behavior analysis and prediction tools. Now the resultant information is used to make informed decisions and design each and every inch of the game.


Game development is very expensive. It requires a lot of funds along with the time. Investors and mother companies do not want to finance the games that do not end well and earn a good profit. So, decisions are being made for the development of the game on the basis of data. If the data that is being collected using surveys, social media or the previous game supports the decision of a new game or not.

For that, the data must be analyzed for the development, deployment, and maintenance of the game as well.

Tidbit: Data science is the reason why Activision released Call of Duty Mobile just for Vietnam and not for the rest of the world so that they can analyze the behavior and interest of the players and make possible amendments before launching everywhere in the world.

Final Words

Either it comes to designing a new game that must fulfill the entertainment and adventure needs of the player or detecting the cheat engines and trainers during the competition, data science has been playing its role in the gaming industry. Now the companies are investing money in the data science field to assure that users may have the optimum experience while playing these games.

After the introduction of this new crucial niche in the gaming industry, it also came with new positions of data scientists and behavioral analysts in the field. All sorts of data analysts and now being trained for the gaming industry that is analyzing the data being produced by multiplayer and online games.

How much the gaming industry has evolved due to data science. Please leave your comments below.


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