[Huawei Developers] Jack Wu Shenzhen:
Data is critical to game apps: it helps game developers get an idea of their audiences and understand their behavior. This in turn can help them make predictions regarding the user churn rate and chances of users making payments and repurchases. Consequently, developers can prevent experience-based decision-making and realize data-driven operations.

Drawbacks of the Self-built Data Platform​

Some enterprises choose to develop their own data platform to realize data-driven development, but this has a number of drawbacks:

1. High costs: A self-built data platform is both expensive and demanding to build.

2. Rigid: Developing such a platform is slow, and cannot flexibly adapt to changing service requirements.

3. Limited data collection: A self-built data platform often overlooks data such as push notification tapping and app uninstallation, meaning some key user data is ignored.

4. Lack of data mining technology: Most self-built data platforms can only complete data statistics because they lack machine learning capabilities. This means that they are not capable of predicting user churn, payment, and repurchase rates. Such platforms thereby hinder decision-making.

5. Insufficient data presentation: A self-built data platform only presents data in a report, without comprehensive functions such as analysis by different dimensions and comparison analysis.

Game Industry Analysis Reports and Event Tracking Templates in Analytics Kit​

Analytics Kit now provides game industry analysis reports, with indicators for MMO and trading card games, as well as event tracking templates and sample code. A report comprises three parts: overview of core indicators, game rules analysis, and player and payment analysis. The kit facilitates integration and event tracking configuration, verification, and management, making it easy to complete all event-tracking-related work in a single day, thereby boosting both efficiency and accuracy. The kit's report covers a range of indicators, allowing you to understand your game's core data anytime and anywhere.

Overview of Core Indicators​

Briefly presents key app data.

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* For reference only

It provides a clear picture of the operations status by showing data for such indicators as yesterday's new users, active users, payment amount, ARPU, and ARPPU, and real-time online players, paying users, and payment rate. If you want to look for specific data, try the filter function to check the numbers of new users and paying users from, say, different regions and channels. Or, you can view the payment amount for new and existing users, if you want.

Game Rules Analysis​

The indicators in game rules analysis will vary from game to game. A trading card game, for example, will focus on card-related indicators, like the number of players drawing cards, card draws, average card draws per player, and rate of players drawing cards. This can tell the game designer all of the relevant information about card draws within the app.

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Most players tend to engage in PvP or PvE battles. Data concerning these gaming options can be found in battle analysis, and includes total battle rounds, battle participation rate, number of players in the battle, and number of battles per player. This can reveal important information about how a battling rule is recognized by players, and can help with making more informed decisions about improving the rule.

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Core indicators for an MMO game include those related to the guild system, life simulation system, and dungeon. The MMO game analysis report shows a range of indicators, like the quantity of each pet, mount, gear, the learning times of each skill, participation status in each dungeon, dungeon participation status of each occupation, number of items earned in dungeons, average number of players in guilds of different levels, number of guilds with activity participation, and average level of guilds.

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* Analysis of the life simulation system

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* Analysis of the dungeon

Player and Payment Analysis​

Player analysis provides a bird's eye view of game players, by displaying indicator data, such as active users, active players, lost players, won-back players, number of players who signed in to the game, sign-in time segments, usage duration, and retention rates of new users and active users.

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* For reference only

Payment and virtual consumption analysis fully displays relevant data for a number of indicators, including the payment amount, number of paying users, payment rate, average payment amount per user, ARPPU, ARPU, day-7 retention rate of paying users, virtual coin earning/consumption overview, and virtual coins consumed by player level/game level/item.

Out-of-the-Box Templates​

To help ensure highly efficient event tracking, Analytics Kit also provides event tracking templates for the game industry, which include sample code. Event tracking can be performed by copying the sample code, downloading the report, or using visual event tracking.

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* Trading card game template

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* MMO game template

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In addition to the game industry analysis report, other analysis models in Analytics Kit can also be used to fully analyze user behavior, giving you a complete picture of new user attraction channels, game rules, and players. For example:

1. Audience segmentation and profile analysis help with optimizing the new user attraction strategy, by creating a profile for highly active core players, and revealing their behavioral characteristics.

2. Attribution analysis assists with improving resource allocation by showing the user payment contribution rate of each resource slot, traffic entry, and operations campaign.

3. Session path analysis helps with analyzing the flow direction of the app launch event for different users and paths leading to payment. When used together with the funnel, this function enables you to locate the root causes leading to user churn, and formulate strategies for optimizing the playing rules and items in the game app.

4. User payment, repurchase, and churn predictions allow you to effectively prevent your app from losing users. On top of this, these predictions can help you identify which users are likely to make purchases in your app, so you can directly target them by sending messages like Time-limited discount and Item comes with limited amount.

With its user-centric approach, Analytics Kit will continue to explore new methods for extracting the most value from data, and empowering enterprises with new capabilities.

To learn more, click here to get the free trial for the demo, or visit our official website to access the development documents for Android, iOS, Web, and Quick App.