Why Data Analytics is the Biggest Player in Game Development – Latest Trends in Digital Transformation | Cloud News

Game development is now leveraging the benefits of data analytics to deliver the best user experience for every player. Data analysis is the analysis of raw data to improve the development of a game. Popular games usually use it, so the number of their players keeps growing.

Here are some of the reasons why data analytics is essential in the gaming industry:

1. Improve game design

One of the important features that make a gamer addicted to a game is its design. Game developers use information from various data sources to deliver great gameplay and graphics. For example, data analysis can show that players in a particular game are more into interactive design. With such information, developers of similar games can apply this information to gain popularity.

Additionally, with creativity, data analysis helps identify games in a design. This means that the developers can use the information on how they can design the game. An example of this is that the game may lack streaming features, which makes it unappealing to players who are streaming the game live. If not resolved, players are likely to quit the game. Cnvrg explains this in more detail about the role of machine learning (ML).

2. Create business models

Game development companies also follow business models, and data analysis is key to ensuring they make better decisions about it. This is because game developers will know what makes a game popular.

For example, if they have an existing game and it doesn’t get enough attention, they can use the data to find out why. Maybe their game is too expensive and other similar games offer freemium which makes the latter more popular. With such data, they can improve their business models and strategies to meet the needs of gamers.

Additionally, game developers are more likely to plan for the long term instead of continuing with their outdated business models. But without data analysis, game developers wouldn’t know how to create a model that would resonate with their target gamers. They might create great business models, but are not suitable for the games they offer.

3. Adjust the difficulty of the game

Another reason why data analysis is essential is to identify the difficulty of the game. Sometimes players may find a game too complicated, which prevents them from leveling up. While this may seem like a challenge, it can also have a negative effect.

For example, if most players end up getting frustrated with their inability to level up, there’s a good chance they’ll stop playing. Thus, analyzing the data will help developers learn about this problem. And they can use player skills and like to change the difficulty of a game.

With such a game, players are more likely to stay and play the game if the difficulty level is just enough to challenge their minds. And with such a compromise, the compromise could make gamers more satisfied with the game.

4. Increase monetization

Although the game companies offer freemium games, they still make a profit. With the help of data analysis, they can perceive which methods would work best. They can collect data from their players so that they can analyze what may bring them profit. For example, data shows that players prefer to upgrade their character’s costumes, weapons, or armor. With this, they are more likely to offer in-app purchases where players who want character upgrades will need to purchase some.

Sometimes players want to remove ads in games to avoid interruptions. For this to happen, they may need to pay a fee to make the game ad-free. But if the data shows gamers are ok with the ads, it may be best to add more ads to the game for monetization purposes.

Another case is when a game has features that are not the highlight of the game. For example, animals in a game are only meant to be displayed, but more and more players interact with them. Game developers will then use this data to monetize the animals by selling them. They can also offer ways for players to breed such species. In this way, not only do game developers make gamers happy, but they also profit from it.

However, as mentioned earlier, it will all depend on the likes and dislikes of the players. What may work as monetization for other games may not work on the type of players you have.

5. Detect fraud

Another important use of data analysis is fraud detection. Many cybercriminals use games to steal money from players or the game itself. Even if they don’t take money, they can cheat the game to win, level up, or “buy” items for free.

And if there are millions of players, it may be too difficult to detect these malicious activities manually. Therefore, players use analyzes using machine learning algorithms to identify such activities. In addition, they can use the data to enhance their security. In this way, players will have a secure platform to share their personal information and transactions.

6. Identify the object

Part of designing a game is making the graphics look realistic. Using image recognition technologies, developers can collect data by revolutionizing game designs. They also use this data to create smooth movement or scene change in the game space. This will enhance the gaming experience for players by integrating virtual and augmented reality.

Game developers are then able to improve game functionality such as giving players commands. He can now do it quickly by identifying objects through data analysis instead of a game taking time to perform player actions.

Conclusion

Back then, game development focused on the aesthetics of a game. But now game designs are only a part of game development, as there are many factors that need to be considered. Now they have to make sure that all the features in a game are what their players like and enjoy. Without it, their players are more likely to find other games available in the market. Consider the ideas mentioned here when using data analytics in game development.


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