Data Science and Analytics in Video Games Development

Over the past few years Data Science and Analytics have become popularized and more and more ingrained in every aspect of our lives. Data science has spread to almost every industry, but there are still a few where it has just hit the surface of, one of which is the gaming industry and the impact of it is growing very fast. The human oriented games are now evolved into data oriented games.  

The gaming industry is on its rise nowadays. With more than 2 billion players all over the world gaming industry is a resource of enormous revenues and these revenues are expected to grow further on. With a growing number of users, the amount of data to be proceeded is enlarging. Users’ playing time, interaction time, quitting point, peaks of activity, results, scores, etc. present vast material for analytics.

New Generation of Data Oriented Gaming 

Use of Data in gaming is to make strategies according to the behavior of the player and constantly collecting data and making predictions and decisions. The new generation of gaming is dependent on data collection by analyzing the behavior of the player and the use of Artificial Intelligence and Machine Learning to for better development.

Gaming Industry – An Opportunity for Data Science

Data Science helps in analyzing the game development strategies. The mathematical model helps in identifying the game optimizing point. The Data Mining technique helps in increasing the efficiency of the game. Transferring human intelligence into artificial intelligence using machine learning tool and data science algorithm in a better way helps the game development company more competitive. Machine Learning tool helps in developing the descriptive, predictive and prescriptive model for better optimization of the condition. Data driven game technology helps to identify meaningful relationships, patterns, trends, and user behavior models from complex data sets to guide service roadmaps and creates automated anomaly detection systems and constantly tracks its performance to increase the user engagement.

Data Science Techniques used in Video Gaming

The understanding of the data value for optimization and improvement of gaming makes specialists search for new ways to apply data science and its benefits in the gaming business. Therefore, various specific data science use cases appear. Here is our list of the most efficient and widely applied data science use cases in gaming.

1.    Game Development:- Game Development is the art of creating games and describes the design, development and release of a game. Data science is utilized to build the models of the game, to analyze and identify optimization points, make predictions and improve gaming models.

2.    Game monetization:- According to video game publisher companies prospective, their goal is to make any game profitable for them. Video game monetization is the process used by the game publisher to generate revenue. Big data analytics tools is used for predictions on behavior and optimization of games in such a way that players will come back again and will be ready to pay money for playing. That will help the publisher company to make sure that the game is profitable for them or not.

Business models to monetize video games:

a)    In retail stores, customers pay for a physical copy of the game.

b)   By the help of Digital distribution or digital download customers buy the game online or download it directly in their device by paying the amount. 

c)    Subscription model is a business model where a game requires continuous, ongoing payments from customers in order to play the game.

d)   Player trading is a business model where in-game items and digital currencies can be traded between players on the game marketplace that allows the publisher to get a cut on transactions that players made.

e)    Advertising is a form of indirect monetization

3.    Game design:- Game design is the art of applying design and aesthetics to create a game. A designer need to be creative to design a powerful game. It is a complex process requiring various programming, visualization, and animation skills. The designer has to play three different roles. Those are in the field of programming, creative writing and graphic design.

4.    Object identification:- Realistic graphics, application of artificial intelligence, image recognition technologies are some main factors that a game developer or a designer should look upon. Game designer also has to understand the behavior of the player.

5.    Visual effects and graphics:- computer graphic techniques create a high impact on the visual effects in gaming. Motion capture in games, real-time rendering, photo-grammetric are some mechanisms used for the development of visual effects and graphics design.

6.    Personalized marketing:- Personalized marketing in gaming helps to increase the activity of the users and at the same time attract new customers. Video games providers collect data from the market analysis that will help to appeal to the audience better.

7.    Fraud detection:- Fraud was nearly always about making money in the fastest way possible for the fraudster, and it was generally divided into two categories:- ‘True fraud’ and ‘Friendly fraud’. True fraud is fraud with the intent to steal money or to knowingly defraud a merchant. Friendly fraud is fraud that usually happens without criminal intent. Therefore, gaming companies need to assure a high level of security to the player’s personal information and transactions performed. Machine learning algorithms help to the rescue of gaming companies to detect the fraud.

8.    Social and customer analysis:- Social data and customer data analysis are essential to understand the customer’s perception of the games and develop effective product strategies. It also helps the gaming industry to get customers insights into their attitude towards the brand and predict customers purchase decisions and brand loyalty. Big Data technology helps the company to gather the data from millions of players and analyze those to get an insight. 

 Advantages of use of Data Analytics in Gaming Industry

1.  Data Science Techniques For Strategic Impact:- Most of the video games need a particular strategy to follow to complete the objective level wise. Good strategies and gaming technique helps in achieving this. The best way the strategy part can be devised by the help of data science techniques.

2.  Capturing The Essence Of Fun:- The most important things a video game company looks is bringing more fun into games by keeping players engaging into the game. In this, the data analytics can help set trends and ensure players return to the gaming platform. 

3.  Data-Driven Game Development:- Data science is no replacement to creativity and design. Having excellent graphics and a better game-play won’t sufficient. Insights from gaming data is highly important to design a successful game.  

Use of Artificial Intelligence & Machine Learning in Video Games

Artificial Intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. 

Machine learning is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. Machine learning helps in analyzing of massive quantities of data. It generally delivers faster, more accurate results in order to identify profitable opportunities as well as risks.

Combining machine learning with AI and cognitive technologies can make it even more effective in processing large volumes of information.

Machine Learning algorithm can help in understanding player’s characteristics dynamically. It also helps the game playing against or alongside human players. It actually connects the dots between ‘human intelligence’ and ‘artificial intelligence’.

Important Features of Machine Learning in game development:

 1. Develop the game algorithm- Machine Learning helps in developing the game in an unique way so that it creates a competitive advantage to all the game development company.

2. Modeling complex system- Machine Learning helps in building a realistic and complex game design by predicting the action and cognitive behavior of the players.

3. Make the game attractive- Machine Learning helps in building the model of the game beautiful by designing the graphics and computer vision more attractive by improving the texture of the game.

4. Realistic interaction- It helps in connecting the virtual world with realistic world by making smooth interaction between the players.

5. Path-finding technique- Machine learning also using path-finding technique by using the maps as a part in game design.

6. Increase human engagement- Machine learning helps to make the game more effective by making it pocket friendly by engaging the players through mobile device. It consolidate the large version of the game into a small version and increase the number of players.

Internet Gaming Disorder

Psychological problems associated with Internet gaming is increasingly recognized as a global problem. The human brain learns and adapts. Numerous research studies have focused on the impact of action video games on the brain by measuring cognitive abilities, such as perception and reaction time. Internet Gaming Disorder is an increasingly prevalent disorder, which can have severe consequences in affected young people and their families. 

The main criteria of ‘Internet gaming disorder’ are:-

1.    Addiction with Internet games.

2.    Withdrawal symptoms when Internet gaming is taken away.

3.    Amounts of time engaged in Internet gaming.

4.    Unsuccessful attempts to control participation in Internet gaming.

5.    Loss of interest in hobbies and entertainment.

6.    Continued excessive use of Internet games despite knowledge of psycho-social problems.

7.    Deception of family members, therapists, or others regarding the amount of Internet gaming.

8.    Use of Internet gaming to escape or relieve a negative mood.

9.    Loss of a significant relationship, job, or educational or career opportunity because of participation in Internet games.

 Conclusion

The gaming industry has been growing exponentially. The number of active users tends to increase every minute and so does the overall income of the companies developing games. The inner infrastructure of the games gets even more complex providing more opportunities for players. An entirely new world and realities are created for the users. Top level visualization and design techniques, the latest visual effects, graphic elements and augmented reality effects provide customers with a high level of satisfaction.

Data science has entered various industries and improved the principles of their functioning forever. It has brought various businesses to a qualitatively new level of their development. The industry of gaming is no exception here. Moreover, data science techniques and methodologies have become integral parts of games development, design, operation, and many other stages of their functioning.