When many people open this brand new task platform for the first time, their instinct is to treat it as a 'task wall': take tasks, complete them, and receive rewards, which seems no fundamentally different from traditional Web2 game activities. However, if you study its design details carefully, you will find that the true goal of the entire system is actually centered around 'reconstructing the early user profile'.

The early user profile of traditional games often relies on advertising data and rough retention statistics, making it impossible to identify whether a player is only coming for rewards, and it is even more difficult to determine who has the real potential to become a core user, content creator, and community backbone. In the new task - Launchpad system, every action is measurable, traceable, and analyzable, thus forming a user profile that is far more sophisticated than 'first-day retention' and 'seven-day retention'.

For example, beginner guide tasks are not just for teaching, but are used to distinguish between shallow users who "just click a few times for rewards" and deep users who are willing to seriously understand the mechanisms; combat or competition-related tasks are used to identify players with high operational skills and strong strategic abilities; tasks that involve participating in governance proposals, feedback surveys, and bug submissions are screening for those who have the potential to become core contributors in the future. All these dimensions add up, and the portrait of a "high-value player" gradually becomes clearer.

When this portrait is used for token distribution in the Launchpad phase, the distribution logic is completely different from the traditional "whoever grabs it first, whoever does it more". You do not win by scripts and studio scale, but by real time investment and behavior quality. For projects, this means that the initial chips are more concentrated in the hands of those who may participate long-term in the game ecosystem, rather than a group of short-term addresses that only want to sell off immediately. This is crucial for stabilizing initial prices, reducing dumping pressure, and extending the game lifecycle.

From the perspective of data products, this platform is more like an "early behavior analysis engine for chain games." It unifies elements such as task design, behavior characteristics, reward weights, and Launchpad allocation within a single logic, serving both project screening users and helping players understand the project. By completing different types of tasks, players are actually actively exposing their preferences: are you more loyal to PVE narratives or do you prefer PVP confrontations; do you value asset appreciation more or do you care more about competitive achievements.

In the future, if this set of behavioral data can be called across projects while respecting privacy, there is an opportunity to build a complete "player credit curve." When you continuously complete tasks, participate in governance, and generate high-quality content in one project, another new project can directly identify you as a "high-value player" during the Launchpad phase, granting more testing slots or higher token allocation weights. This will form a positive feedback loop: those who play games seriously and participate in the ecosystem will enjoy a higher starting point and lower trial-and-error costs throughout the entire chain game field.

For ordinary players, understanding this is very important: tasks are no longer just about completing them for a reward; they are accumulating credit for your future "player resume." You can selectively participate in projects you truly believe in, investing your limited time in more promising gameplay and worldviews, rather than mechanically completing tasks on any platform you encounter.

When the Launchpad begins to allocate early rights based on "behavior quality" and "long-term participation," the ecosystem of chain games will have taken a crucial step from barbaric growth to refined operation.

@Yield Guild Games #YGGPlay $YGG

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