Data Science in Gaming Industry
As we all know, big data, in general, is associated with mathematical models and statistics, programming and computer science. But apart from that, it also relates to other aspects of the IT-related fields, such as gaming, gambling, banking, and global financial industries. Big data helps to understand the finer nuances of the problems that appear in these domains and apply right solutions in practice. In this article, we would like to talk about data science application in the gaming industry.
Gaming Market Review
Let’s take a look at the gaming market in terms of how much time people spend there and the market value globally. Based on the Statista’s data we can see that DOTA 2 is by far the leader in the average number of players engaged per hour reaching a mark of more than 636 thousand active users.
On the other hand, you can see that the second place is held by the Counter Strike: GO with a result of 360 thousand players, and the “Team Fortress 2” completes the top three with 50 thousand.
From the financial perspective, the market does not seem to suffer at all: 2016 brought about $75 billion to the developers and by 2020 this figure could as well amount to $90 billion.
By gathering and analyzing information about all in-game users and their interactions, it is possible to introduce new strategies and activities to the development process of the certain gaming product. And all of these can be done with the help of data science and its analytics tools.
Data Science Impact on the Gaming Industry
Among the main aspects of the gaming industry that undoubtedly felt the impact of the big data technologies the following are identified:
Loads and balancing. Collecting and analyzing information about the number of users (on different platforms) and their general time in-game, you can scale the load on servers;
Big data for making more money on advertising. Targeted advertising can greatly affect in-game purchases, as well as provide great means for introduction of the new products;
Big data for optimizing the gaming experience. The data science can show the most “narrow” moments of gameplay after which users lose their interest. Thus, it is possible to react to the problem at an early stage and grab a hold of the audience allowing players to help improve the in-game experience simultaneously.
Data Science and Games: Use Cases
To understand how data science can impact the game development industry (both in terms of improving mechanics and in terms of attracting users), let’s take a look at some specific examples.
Microtransactions in Zynga
Microtransactions and advertising in games is an indispensable attribute of online gaming today. An exemplary item would be Zynga with its monetization scheme. The employment of the microtransactions allows users getting small bonuses or boosts that help bypass difficult moments or speed up the game completion process. On the other hand, it is possible to use sponsorship support from large vendors in the form of special in-game tasks which can bring additional game points when performed. The sponsor companies, in turn, receive some “broadcasting time” for advertising.
Data Mining in Minecraft
Today, the gaming industry can be regarded as a huge source of data that can be analyzed to help you attract even more gamers. In fact, each individual in-game action, as well as the interval of pressing buttons or even human behavior (e.g., based on their feedback) can be analyzed. Not long ago, Microsoft purchased Minecraft, presumably for such purposes. This particular case is an example of direct data capture with the purpose of analyzing the players’ behavior outside the entertainment area.
According to Satista’s data for June 2016 – February 2017, the number of active Minecraft players increased from 40 to 55 million, respectively. Thus, the game provides a lot of data for analysis as it consists of many items that are created by the special “recipes”. Millions of players interact with both the in-game world and among themselves online manipulating virtual objects to achieve specific goals. Microsoft believes that Minecraft can help children transfer the gaming experience into the real life by evaluating the interactions with digital data in the game.
Today gaming industry can be considered as a huge source of data that can be analyzed to attract even more gamers. In fact, each individual in-game action, as well as the interval of pressing buttons or human behavior can be analyzed, giving feedback.
Improving Gamer Experience in Games by Electronic Arts (EA)
In 2013, EA Games received the title of the most terrible company, but today, they are considered to be among the most successful gaming companies again. For several years, the corporation used data science to collect and analyze details. Data analytics tools helped to monitor players’ behavior which indicated how acceptable or difficult the certain part of the game can be, what they like and dislike. Thus, using new approaches to data analysis, the company managed to regain the leading positions in the market.
Fraud Detection in Gaming: Case Study
Relying on experience and the particular cases, we can personally confirm that data science could be applied to the entertainment industry to enhance security and improve project’s monetization. In particular, through identifying players’ behavior in a certain game situation and their time spent in-game, as well as the artificial intelligence reaction to different activities.
In order to fight off the suspicious and fraudulent activities, the algorithms that track counterfeit cards and add them to the database (to minimize repeated entries) were developed. With the help of machine learning, it is possible to identify the owners of several gaming accounts and also suspicious fund transfers.
If to take into account big companies that are working to introduce and improve security systems in games, Valve should be mentioned first. Their Valve Anti-Cheat System (VAC) is used in games developed by the company itself and many other third-party products. Another big company that takes advantage of the big data approach to improve its services is EA Games, which use this method to lay the basis of their games.
Players always leave their mark, from the moment they connect to the game, sign in into sessions and perform in-game actions. And all such activities are registered by the system for further analysis. Thus, a large amount of data can give certain indicators in the players’ behavior and determine suspicious actions on this basis.
You can read more about our expertise on fraud detection in the gaming industry here.
At the forefront of improvement are risk management and identification of the exact target audience (using big data for driving customer engagement). Moreover, speaking about the financial side of the issue, it became possible to identify fraudulent transactions, as well as various types of in-game fraudulent actions. Thus, considering all the described above, a conclusion can be made that the current data science’s impact on the gaming industry is huge.
If you want to get more information about data science in the gaming industry or interested how big data can help your business, don’t hesitate and contact us at email@example.com.