5 Best Uses Of Data Science In Gaming

Data Science In Gaming:

The gaming industry is super huge. There is no denying that. According to industry statistics, The Gaming Market was valued at USD 198.40 billion in 2021, and it is expected to reach a value of USD 339.95 billion by 2027, registering a CAGR(Compound Annual Growth Rate) of 8.94% over 2022-2027. Due to nationwide lockdowns implemented because of the COVID-19 pandemic, some people turned to game platforms to pass the time.

Where is Data Science used In Gaming?

Data Science is used in almost all the stages of Game Development. Let’s see where we use data science in gaming.

Development:

The gaming industry wants you to be addicted to the games. The more you purchase their add-ons, downloaded and spend time on them, the more successful their game is. But how are they going to achieve it?

Here Comes Data Science. Gaming Companies have lots of data on players, like the levels they played more, the levels they quit on, how long they play a certain game, and many more.

This Data is used by analysts to build the whole model, functionality to keep players engaged all the time.

Most of the games don’t let you see the data that you created but there is a particular Gaming Web app Data Games.

Improvement In Versions:

data science in gaming

Have you ever noticed that most of Version2 of a game is better than Version1? Why is that? How do they know what features we wanted them to add or remove? Every time you are playing, you are creating data for them to analyze and improve themselves. Not only this, every game that is uploaded to the play store gets reviews.

Reviews are analyzed and specific keywords, suggestions, and feedback are extracted, and calculated so that we know what is missing in our games.

Identifying An Object:

Image Recognition Technology is playing a huge role in Gaming Industry. Recognizing Real objects and using them in games gives players the real feel of it.

data science in gaming

Fraud Detection :

There are many Hackers in this field, who somehow find their way to find a loophole to win and that is unfair to other players. Data Science and machine learning play an important role to analyze fraud and block him from playing. We use Machine learning to predict fraudulent behavior in online casino settings.

Customer Analysis:

The gaming industry increasing exponentially. Each second millions of customers are joining and generating a huge amount of valuable data, that is useful to improve the product and marketing strategies.

What do Gaming Data Analysts Do?

Assembles data from multiple sources, conducts analyses, performs research, designs, documents and implements analytical solutions.
Presents analysis conclusions to the internal customer in a clear, understandable, and valuable way.
Communicates with team members and business stakeholders.
Presents high-quality reports and findings in Power BI or as presentations.
Builds metrics reporting systems and tracks process improvements across the team.
Conducts analysis using statistical software, databases, spreadsheets, and reporting tools
Designs, evaluate, and monitor key metrics, understanding root causes of changes in metrics
Develops and maintains scripts and queries to import, manipulate, clean, transform data from different sources
Builds and shares live dashboards and report complete with user documentation
Builds and trains statistical models for hypothesis testing
Performs quality assurance on generated results to ensure accuracy and consistency
Presents conclusions in a clear and concise way