How Analytics and Machine Learning Make Games Profitable?

The gaming industry has exploded – today, there are over 2 billion active players around the world. Naturally, so many users lead to huge revenues that we expect to grow further in the future. As the number of users keeps growing, however, so does the amount of data.

Data has become a vital factor in modern business. Companies are no longer making business decisions based on intuition or experience. They need to gather information and analyze it thoroughly so that they can make sound decisions based on relevant data.

In the gaming world, things like interaction time, scores, results, gamer activity, quitting percentage, and others can lead to some valuable conclusions.

Today we are going to talk about how analytics and machine learning are used to help go through all of this data faster and improve the bottom line. 

Why gaming data matters

Most of us don’t think about data when someone mentions games. Instead, we think about game mechanics, the story behind the game, or strategies that can be used.

However, data is at the center of all games. When a player is enjoying their favorite game, they are continually gathering data consciously or subconsciously.

Based on it, games have players make new decisions. The same principle can be applied to the gaming industry’s point of view. These companies can also use this data to make predictions and future decisions for developing games that players will love more.

Not only that, this medium is full of data, but it can also be accessed easily. It’s where analytics and machine learning can be easily implemented to improve business results.

On top of that, it’s a great environment where developers can try out different theories and test out algorithms.

Recognizing key marketing areas

Like in any industry, marketing plays a vital role in gaming towards increasing profits. However, marketing a particular game is not an easy job.

It’s important to know where to target your marketing efforts, in what way, and to which audiences. Not all gamers are the same, nor do they like the same games.

It’s essential to know the value of every player along with influential gamers or streamers on Mixer or Twitch. It can help you decide where to target your personalized marketing. With machine learning, you can analyze your market and figure out the market for your game.

At the same time, machine learning and analytics can help you segment your target audience by helping you determine which gamers are likely to play your game for a longer time.

That way, you can prioritize your marketing efforts and build a steady base of players early on.

Making the games more fun

Games are all about fun, and every player will tell you that. However, it’s not easy to develop a new and fun game that players will fall in love with.

There are so many games out there, and players have tried out many things. That’s is why creating something that will bring them the kind of joy they felt when they first started playing games is difficult.

Developers can find answers for this in gaming data. Since there is more and more gaming data generated on the web, data analytics and machine learning can be used to spot trends and set them. As a result, this will help keep players on a certain platform much longer, thus maintaining revenue.

With various tools powered by machine learning and other technologies like AI, companies can track player behavior. They know how much players play the game, where they shut the game down, and when they quit.

They can also establish a pattern of behavior and see what players like the most. All these insights can help reach valuable conclusions in terms of what is fun in a game.

Analyzing streaming statistics

There are many influential gamers called “streamers” that have live broadcasts of how they play games.

Their live streams on YouTube, Twitch, and other gaming platforms build communities of followers. Within this group of followers, there are a lot of people who can easily be turned into players.

By analyzing streaming statistics of streamers who play similar games or a game that’s already been released, companies can learn a lot. They can see what players enjoy in those games and what the whole community has to say about it, their positives and negatives.

On top of that, game development companies can also recognize which influencers have the best audiences for their future releases. It allows them to focus their marketing and get a higher ROI.

Improved behavioral analytics through machine learning

All gaming companies try to engage new players and retain them for a long time to directly increase their profits.

Machine learning has enabled companies with behavioral analytics capabilities to identify the accurate population of gamers and attract them with proper content placement.

On the other hand, they can also learn what makes gamers play a specific game for an extended time. All these results are later used by developers to improve their game design and create an even better gaming experience.

Furthermore, behavioral analytics can help find a group of gamers that have similar characteristics and promote new content to them. Machine learning can source a lot of this kind of data daily and always provide relevant information.

On top of that, it can also do predictive analytics to project future trends based on current information. However, this requires a lot of resources and full-time commitment. That’s why a lot of gaming companies have their data entry outsourced to save valuable resources. 

Conclusion

Games are a form of creative art. They need to have that spark of joy that players love. However, adding data into the mix can help enhance all those creative aspects of the gaming experience. We live in a new age of gaming, and we can’t wait to see what the future holds.