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How Is Data Science Used In Game Development?

Data Science In Game Development
Image Source: Analytics Vidhya

Degrees in Data Science are the most lucrative in the world, helping students land the best jobs today.

People often associate mundane, highly-cranial, less-creative, no-fun images with data science, which can’t be further from the truth. Data scientists can be involved in a myriad of exciting and innovation-seeking jobs like game development, product development, robotics, and more.  

This article will narrow down on gaming development and how data science is involved in it. 

Five ways data science is used in game development 

Here are five ways how game development leverages the power of data:

1. Engaging Game Design

Game design is an elaborate and foundationally important process requiring various data analysis, programming, visualization, and animation skills. There has to be a balance between creativity, a sense of aesthetics, and leveraging data and technology. Data analysis in game design is used to identify game optimization points in developing game themes, difficulty levels, storylines, scenarios, game mechanics, and characters. 

This is also one of the main reasons why video game companies conduct Focus Groups, Close Beta Tests, and Open Beta Tests. These groups help them garner a lot of data and make informed decisions thereafter. These data can help game developers develop a game that keeps its players hooked for a longer time. For example, data can answer questions like:

  • How do the players interact with the game?
  • How do the players like to traverse in the game? 
  • What kinds of characters are players using and why? 
  • What do they not like about the game?

This can help in adding and removing new game features and make other changes in the game design. Game developers can predict gaming bottlenecks, optimize concepts and storylines and give people what the player wants and who better to understand the needs of gamers than gamers themselves? This is one of the major pros of having a data science degree if you are into gaming since you will be able to create the kind of games you would actually want yourself to play.  

2. Player demographics

Knowing player demographics keeps game developers and marketers from shooting in the dark. Just like any other business, the product or the service has to revolve and rotate around the user and change with time. To do this, game makers need to have elaborate data sets on who their customers are, or more precisely, have information on who their average player is – this is known as a buyer persona

This information includes:

  • Sex
  • Age
  • Location
  • Profession, and 
  • Playing habits (time of day they usually play, do they play daily or only on weekends, how long their sessions are, etc.) 

Big data analytics tools will process this data and ensure that your game is catering to the needs of its players or not.

How do you collect this customer demographics data?

There are many ways to connect demographic data of customers:

Game developers can gather data from social network activity, general playing activity, and overtly recorded customer feedback to segment your players and study their preferences and behavior.

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This data collected is useful and predicts the behavior of the gamers. Optimizing games in such a way are used for predictions on behavior and optimization of games to increase the stickiness of the game.

3. Monetizing the game

Here are a few points to note any talk about data science and now it helps monetize a game:

Data-driven, money-making decisions 

The end game is always to earn monetary profits out of the game created. Data science tools can help analyze data to determine which features are in demand, in other words, which features customers will be willing to pay for. 

Data can help you create strategies to make free players pay for additional features or premium membership. 

Personalized recommendations 

Gaming platforms can use recommendation engines that leverage the power of Artificial Intelligence and Machine Learning and learn from the gamer’s behavior on the platform. So, the next time the gamer logs in, they are shown a series of recommended games based on their past behavior only. 

Smart AI-driven recommendation engines can drastically improve the chances of game developers to find the audience interested in their games and thus get massive ROIs.

Targeting with Personalized In-app Ads

Another big way to monetize games is through in-app ads. However, these ads need to be relevant to the gamers to reduce the quality of their customer experience and clicks.

Both the game developers and marketers are interested in highly targeted interaction with customers and lead by the creation of meaningful marketing messages and delivering them to proper people. 

Personalized marketing is driven only by data, and it helps in gaming to increase the activity of the users and at the same time attract new ones. For instance, ads based on past searches, interests, and behavior on websites would be key to effectively monetizing gaming apps. 

4. Analyzing player feedback

Most games have a rating system and request reviews from users. The insights gleaned from this feedback can help developers tweak and improve the game. 

Game developers can use the following methods to conduct surveys and gather data from the players:

Net Promoter Score (NPS): Used to find who all like your products//services and will refer them to others. For example, from 1 to 10, how likely are you to recommend this game to others?

Customer Satisfaction Score (CSAT): Used to find how satisfied customers are with your products and services. E.g., How satisfied are you with the game?

Here are other ways for gamers to gather real-time gamer feedback, compiled by Feature Upvote, a feedback data collecting software. 

5. Security and fraud detection

Player verification systems help prevent identity theft and block scammers from accessing accounts and sensitive information like payment information. In addition, machine learning algorithms are deployed to detect suspicious activity and prevent fraud attempts.

Moreover, payment fraud is also very common in gaming. Fraudsters tend to create special bots to covertly get the payment from other people’s apps. This makes it important for gaming companies to ensure a high level of security to the player’s personal information and transactions are performed.

In sum, if you love gaming and coding, then a degree in data science would certainly prove to be the most rewarding option for you. 

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