Game development is now reaping the benefits of data analytics to provide the best user experience for each gamer. Data analytics involves analyzing raw data to improve the development of a game. Popular games usually use this, so the number of their players would keep on growing.
Below are some of the reasons why data analytics is essential in the gaming industry:
1. Improve Game Design
One of the significant features that make a player hooked in a game is its design. Game developers use the insights from various sources of data to come up with excellent gameplay and graphics. For instance, data analytics may show that players of a particular game are more into interactive design. With such information, developers of similar games may apply such insights to gain more traction.
Moreover, together with creativity, data analytics supports it to identify the games in a design. This means developers can use the insights on how they can design the game. An example of this is that the game may lack streaming features, making it unattractive to players who are live streaming the game. If unsolved, gamers are likely to abandon the game. Cnvrg explains this further concerning the role of machine learning (ML).
2. Create Business Models
Game development companies also follow business models, and data analytics is essential to ensure that they make better decisions when it comes to such. That’s because game developers will know what makes a game popular.
For instance, if they have an existing game and it’s not gaining enough attention, they can use the data to find out why. Maybe their game is too expensive, and other similar games offer freemium, making the latter more popular. With such data, they can improve their business models and strategies to cater to the players’ needs.
Moreover, game developers are more likely to plan for the long-term instead of continuing their outdated business models. But without data analytics, game developers wouldn’t know how to create a model that’ll resonate with their target players. They might be making great business models, but not appropriate for the games they’re offering.
3. Adjust Game Difficulty
Another reason why data analytics is essential is to identify the difficulty of the game. Sometimes, players might find a game too complicated, making them unable to level up. While this may seem a challenge, it can also have a negative effect.
For instance, if most players end up frustrated because of their inability to level up, chances are they’ll stop playing the game. Thus, data analytics will help developers learn about this issue. And they can use the player’s skills and likes to tweak a game’s difficulty.
With such, players are more likely to stay and play the game if the difficulty level is just enough to challenge their spirits. And with such, the tradeoff could make players more satisfied with the game.
4. Increase Monetization
Although gaming companies offer freemium games, they still gain profits. With the help of data analytics, they can perceive what methods would work best. They can collect data from their players so they can analyze what can bring profits for them. For instance, data shows that gamers prefer upgrading their character’s suits, weapons, or armors. With such, they’re more likely to offer in-app purchases wherein players who want character upgrades will have to buy such.
At times, players would want to remove ads in the games to avoid interruptions. For it to happen, they may have to pay some fee to make the game ad-free. But if data shows that players are okay with ads, it may be better to add more advertisements to the game for monetization purposes.
Another instance is when a game has some features that aren’t the highlight of the game. For example, the animals in a game are only for display, but more gamers are interacting with them. Game developers will then use such data to monetize the animals by selling them. They may also offer ways that the players can breed such species. That way not only are game developers making players happy, but they’re also gaining from such.
However, as mentioned earlier, this will all depend on the players’ likes and dislikes. What may work as monetization for other games may not work on the kind of players you have.
5. Detect Fraud
Another important use of data analytics is in fraud detection. Many cyber criminals use games to steal money from the gamers or from the game itself. Even if they don’t take money, they can defraud the game to win, level up, or ‘purchase’ items for free.
And if there are millions of players, it may be too hard to detect such malicious activities manually. Hence, gamers use analytics with the help of machine learning algorithms to identify such activities. In addition, they can use the data to tighten their security. That way, players will have a safe platform to share their personal information and transactions.
6. Identifies Object
Part of designing a game is to make graphics realistic. By using image recognition technologies, developers can collect data from revolutionizing game designs. They also use such data to create smooth movement or change of scenes in the gaming space. Doing so will enhance the gaming experience of the players as it integrates virtual and augmented reality.
Game developers are then able to improve game functionalities such as players giving commands. It can now quickly perform such thanks to object identification through data analytics instead of a game taking time to execute the player’s actions.
Conclusion
Back then, game development focused on the aesthetics of a game. But now, game designs are only part of game development because there are many factors to consider. They now have to ensure that all features of a game are what their players like and enjoy. Without such, their players are more likely to find other games available in the market. Consider the ideas mentioned here as you utilize data analytics in game development.
