Game analytics is a core factor in the life of every game developer, regardless of whether you’re an employee at a startup or an established corporation like Konami. No matter how big the development team is, game analytics will be incredibly valuable. 

This piece will focus on exploring game analytics in terms of analyzing data from different reports, deciding on metrics you want to monitor, and more. 

Meaning of Gaming Analytics and Why You Need it 

Consider game analytics as a method for gathering data from various participants. The information gathered is then utilized to improve the game so that players will be happy, and it will last longer. 

To put it simply, it is a technique for analyzing player behavior using analytics. Key reasons why you need game analytics as a marketer: 

  • It reveals your game’s overall performance, both now and in the future. 
  • It aids in the comprehension of your audience’s wants and preferences. 
  • It reveals how long users spend playing your game. 

Value Added Tips: Top Game Analytics Tools that you can’t avoid 

Choosing the Right Game Analytics Solution  

If you’re a novice, integrating with a game analytics solution that analyzes certain standard metrics is an excellent place to start. This will make the concept easier for you to understand. 

Notable among these metrics are retention rates, click-through rates, and how frequently users interact with your game.  

All these metrics come together to give the developer insights on how to make the game more engaging and exciting for users. 

Setting up an account on the platform you wish to utilize is the first step in using an analytics solution. You can accomplish this by completing a straightforward signup procedure.  

However, if you already have an account with another analytics platform, you could use the import function to transfer your data into the new platform.  

Deciding on What Metrics to Track 

Other analytics fields may regard productivity as a yardstick for success, but Game analytics prioritizes user behavior. This is because games are created specifically for users. 

However, the decision of what Metrics to monitor greatly depends on your target. It could either be to improve user experience, or boost revenue. For instance, if you want to boost revenues, the following metrics should be given priority: 

  • Monetization 
  • Number of daily active users (DAU). 
  • Time used in a game session. 
  • Average income per active user. 

However, if you’re looking to enhance user experience, then you can consider these: time used for players to finish a level, player victories and defeats, and time used by the player on a session. 

Generating Reports  

Once you’re sure about what metrics you want to monitor, what follows next is generating a report for the categories. The following are the four major phases of game analytics: 

1. Descriptive Analysis

Companies are encouraged to always start with this phase since it’s the easiest to implement. They mostly use pie charts, bar charts, tables, and graphs to present the data. 

At this phase, historical events are examined while searching for certain patterns in the data. This phase of analysis strives to answer the question, “what happened?”. 

The most popular type of analytics is descriptive; it converts raw data into reports that are understandable to humans. In GA, descriptive analytics helps game developers to know the number of game players.  

2. Diagnostic Analysis

Usually, after obtaining descriptive insights, a company may use diagnostics with a little extra effort. 

This phase answers the question, “why?”. This is because it’s customary to know what happened before proceeding to understand why it happened. 

The processes here range from data discovery to data mining and more. 

3. Predictive Analysis

Once a company has a thorough understanding of what transpired and why, the predictive phase follows.  

It gives an insight into what’s likely to happen and uses processes such as forecasting, pattern matching, and more to analyze data. 

In gaming analytics, the predictive phase can forecast things like a player’s lifetime worth or their chance of reaching the endgame. 

4. Prescriptive Analysis

Upon knowing what to expect, the prescriptive phase follows and it’s the most advanced phase. The processes involved here to analyze data include machine learning, simulation, graph analysis, and more. 

This phase is usually the most difficult because its success is strictly determined by the accuracy of the previous three phases. 

The prescriptive phase in gaming analytics enables game developers to monitor the results of player choices and plan how to encourage them to make particular choices.  

Not sure how to make your game popular? Check out the interesting step by step process of analyzing your games

Analyzing the Data from Reports   

After generating your reports, what follows is data analysis using the following metrics: 

1. Player Retention

Knowing what features of the game inspires gamers to keep playing is helpful because that’s what will keep them coming for more. 

2. Conversion rate

It computes the portion of how many users out of the total users have purchased your game at the given period. Also, you can track the effectiveness of the adverts shown in free games. 

3. User retention

This metric informs you of the number of users who returned to your app or game throughout a specified time frame. It’s also crucial to your user acquisition approach. 

4. User acquisition

It enables you to evaluate the success of marketing initiatives and tactics like adverts in other games. It is also known as Cost Per Install. 

5. Engagement metrics

This will give you an insight into the level of satisfaction of the players with your game. With this, you’ll know what necessary adjustments to make. 

Making Key Decisions 

Below are practical ways in which the following metrics can impact your decision-making: 


For instance, consider the first, third, and seventh days of retention. If your retention on the first day is impressive, it’s advisable to monitor that of the seventh day in comparison to the first day.  

The customary yardstick for success here would be to have at least half of day 1. This implies that anything below 50% on the first day means the players don’t have enough reason to continue playing your game. 

Engagement metrics

Gamers who find your game engaging are more inclined to return to your game frequently, play for longer periods of time, and spend money there. 

For instance, one can say a gamer who spends a lot of time on a roleplaying game while interacting with other gamers is engaged. 

Using graphs and dashboards to track this data will allow you to modify your strategy. Also, you can determine the elements of the gameplay that are most engaging or otherwise. 

As a leading game service provider, we would love to showcase our case study of Game Analytics for a Metaverse company


Every employee at a firm ought to be aware of how their activities impact revenue-focused results at any given time. The fast-paced evolution of the video game market puts pressure on gaming firms to provide. Players have a seemingly endless array of alternatives for how to spend their limited spare time. 

And since the objective of games is to provide luxury for people, it is crucial to remember that user experience is a key element that determines a game’s success. The decisions you make now regarding your game analytics strategy will establish the foundation for the continued success of your company in the future. 

Inquire Now to explore end-to-end gaming services from the Gaming Giant, iXie! 

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