Making game data analysis possible for the layperson! Why game data analysis is necessary

How many of the following terminologies do you know?

DAU   MAU   ARPU  ARPPU   Retention  LTV

They are basic indicators you should be aware of to conduct game data analysis.

  • DAU (Daily Active Users) Number of users who play the game in a day
  • MAU (Monthly Active Users) Number of users who play the game in a month
  • ARPPU (Average Revenue per Paying User) Average revenue per 1 paying user
  • Retention The retention rate is usually calculated for 1, 7, and 30 days.
  • LTV (Lifetime Value) The average cost paid by 1 user before moving on

Was it too easy? Do you know how to calculate it?

  • ARPPU Total sales / Number of paying users
  • Retention Number of users remaining on Day N / Number of users who played the game on Day 0
  • LTV ARPU x bounce rate

Other useful indicators include organic users, non-organic users, new users, ARPU, and conversion rate. These indicators, which can be easily obtained even without the help of separate analytical tools, reveal whether the problem lies in marketing, user acquisition, the game itself, or inadequate BM. Problematic areas and directions for improvement can be determined based on objective data, instead of relying on subjective judgment or intuition.

The aforementioned marketing indicators are of great importance and easy to use, which has made them widespread. However, they are not at all helpful when it comes to game design and operation. They do not provide specifics on game balance, the causes of users leaving, bounce zones, and actions that can be taken to improve retention. To address such issues, it is first necessary to analyze user behavior, covering areas such as the acquisition and use of game money, the acquisition and use of items, and stage clear/fail. Usually, an analytics tool is required for such analysis.

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How to begin game data analysis?

While major companies have their own data team, most others would rely on commercially available analytics tools. Among the various tools like Firebase, Unity Analytics, PlayFab, and TentuPlay, choose one that best fits your needs. The tools are slightly different, but generally follow the process below.

1. Install SDK
2. Set indicators
3. Set segments
4. Log custom events
5. Check analysis results
6. Establish and implement measures for improvement

Steps 2 through 4 are likely to be the more challenging areas for game companies that lack human resources or amateurs with little knowledge of data analysis.

2. Set indicators
If you are not a professional data analyst, it is not easy to determine what to measure and make into indicators in order to analyze bounce rate and game balance.

3. Set segments
User segmentation is the grouping of users based on shared characteristics. Some examples are paying users, non-paying users, users in the 10–19 age group, and users in the 20–29 age group. Grouping users in this way makes it easier to provide customized services. Users can be grouped based on gender, age, region, or payment, but segmentation based on user behavior is more effective for data analysis. Without expert knowledge on behavioral economics or data analysis, it is extremely difficult to systematize and validate segmentation criteria.

4. Log custom events
A custom event log must be created for each user behavior that you wish to analyze. When making a single purchase event, you have to set up the various parameters and entities. Even if there are recommended templates, they must be modified to fit your game. For many developers, custom event logging can be quite a headache.

 

 

Game data analysis for the layperson

Anyone, even without expert knowledge or sufficient time to spend on data analysis, can conduct quality user analysis by choosing the right AI tool.

1. Install SDK
2. Set indicators → AI
3. Set segments→ AI
4. Log custom events→ AI
5. Check analysis results
6. Establish and implement measures for improvement→ AI

Developers without relevant knowledge or experience can easily carry out professional game analysis using TentuPlay, which uses AI for indicator setting, segment setting, and event logging. SDK installation and results viewing have been designed to be as simple as possible, and the final step for the establishment and implementation of measures for improvement is also automated. Just by installing the SDK, developers can conveniently perform user analysis and improve user experience through customized services.

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1. Install SDK
The SDK takes six hours per average developer. You may request a customized SDK plan for easier installation.

5. Check analysis results
The dashboard is designed so that the analysis results can be easily understood by anyone, even without knowledge of game analysis. The results are presented for each user segment, thereby offering valuable insights into specific user groups.

6. Establish and implement measures for improvement
TentuPlay provides a custom play guide by segment and recommends customized items through in-game messages. Since the templates are automatically generated by the TentuPlay AI, all developers have to do is to customize the message UIs. The play guides help to enhance user enjoyment, and item recommendations lead to higher purchase rates.

 

TentuPlay is a simple and convenient solution that improves conversion rate and revenue by suggesting user-customized purchases. Begin your game data analysis with AI today!

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