Author: Shenchao TechFlow
Recently, Kaito Yap frequently appeared on Twitter, becoming a hot topic for many KOLs to discuss and even "fight over".
Kaito is an AI-based cryptocurrency data analysis platform that recently launched a product called "Yap to Earn", which simply means earning points by posting high-quality tweets. Users can earn Yap points through posting, interaction, and other means, and many expect these points may convert into project tokens in the future.
More importantly, Kaito has established a set of AI scoring evaluation mechanisms for cryptocurrency KOLs, allowing for the dynamic ranking of well-known cryptocurrency influencers.
It is important to note that Kaito Yap has two unique mechanisms:
First, maintain mystery; the specific scoring criteria and basis are not publicly disclosed, and there are no clear scoring guidelines. This black box strategy has its advantages.
Maintaining project mystery avoids complaints related to score calculations, reduces ineffective disputes, and promotes users to continue exploring and innovating, somewhat preventing targeted score boosting.
Secondly, everything is AI-driven. Kaito officials only provide prompts to the AI, which then conducts scoring and screening.
Perhaps it’s 'AI Help AI' (just joking), the top of the CT Yapper leaderboard has long been occupied by the cryptocurrency research AI AGENT Aixbt, demonstrating content creation capabilities that exceed 99% of human users.
This scoring mechanism has its supporters and detractors; many cryptocurrency KOLs who previously focused on project reviews have begun actively competing for points.
However, controversies and doubts have also arisen.
Clarifying the issue vs. algorithmic discrimination
The bottom line determines the perspective; from the project party’s viewpoint, they prefer products that are popular and well-received. Essentially, Kaito's product can be considered a B2B marketing service.
Nowadays, KOL marketing has become a must for many cryptocurrency projects, but the quality of KOLs varies widely, and traditional fan counts and interaction volumes fail to truly reflect KOL value.
The interference of many paid accounts and bots disrupts the information ecosystem, making it difficult for project parties to accurately assess the real influence of KOLs, resulting in uncertain marketing resource effectiveness.
Provide a set of quantifiable KOL selection criteria for project parties, considered a breakthrough attempt in Web3 marketing.
Some support this mechanism, believing that the emergence of Kaito Yap represents not only the birth of a points system but also a new direction for Web3 social media, where value orientation replaces traffic orientation, professional creation surpasses fast food content, helping to discover truly high-quality creators, while also compelling the KOL group to enhance professionalism, positively impacting the overall cryptocurrency information dissemination ecology.
At the same time, Kaito Yap is facing skepticism from KOLs and retail investors.
Shenchao TechFlow summarized that it can be divided into the following categories:
(1) Circle effect: forming a closed ecology monopolized by the "core circle"
Kaito Yap scores tend to favor top KOLs, with core circles supporting each other, making it difficult for newcomers to break into high-score circles. New creators, even if they produce high-quality content, also find it hard to obtain scores similar to those of major influencers, and more importantly, the "circle interaction". Therefore, Kaito Yap is more of a game for major influencers, irrelevant to ordinary people.
(2) Algorithmic discrimination: questioned for discriminating against non-English content
There are KOL feedbacks indicating that compared to English content, non-English cryptocurrency bloggers often receive lower scores, and the value of localized content is underestimated.
In addition, compared to purely amateur accounts, cryptocurrency KOLs with backgrounds from large institutions receive greater weight.
(3) Data limitations
Currently, relying solely on public Twitter data lacks community interaction data, ignoring the value of private traffic; for example, some KOLs who are very active in Telegram groups perform poorly in Yap scoring.
In response to the criticism that the Kaito algorithm discriminates against Chinese content, Kaito staff stated, "The AI trained with the same set of prompts considers your content not solid if it’s not solid, it may be wrong but it’s fair to everyone. There is no claim in the prompts that any Chinese content is automatically downgraded; if you think the Chinese effect is poor, then the content effect is poor."
Despite some doubts, in my view, Kaito is exploring a differentiated development path in the Web3 social field through its points mechanism and community operation strategy. This is a positive innovation that deserves encouragement, but as a growing platform, Kaito still faces some issues that need to be considered and resolved.
How to expand the user base while maintaining professionalism, giving more opportunities to newcomers
Sustainability of the points mechanism
Continuous cultivation of community atmosphere and user stickiness
In the future, with the continuous development of Web3 social domains and AI, the evolutionary direction of emerging platforms like Kaito is worth continued attention.
Finally, Shenchao TechFlow has also summarized a set of Kaito Yap scoring system strategies based on the experiences of some KOLs on Twitter, for reference only.
(1) Principles: Anti-spam content
The official statement clearly indicates resistance to spam content and volume manipulation, with repetitive and valueless posts receiving zero points.
In summary, quality is far more important than quantity.
(2) Focus on hot projects
Pay special attention to the projects on the Kaito panel:
Kaito;
Berachain;
Monad;
Xion;
Paradadex;
Eclipse;
Note: Simply mentioning these project names will not earn points; the key lies in providing valuable analysis and insights.
(3) Quality of interaction is paramount
In addition to focusing on content publishing, Kaito particularly emphasizes interaction with content, especially interaction with high-quality accounts, such as receiving replies from influential users and genuine effective likes.
(4) Precise interaction strategy
Suggestion:
Follow and reply to major influencer accounts;
Participate in high-quality thematic discussions;
Engage in dialogue under highly interactive posts;
Maintain interaction with leaderboard users;
Balance interaction frequency with content quality;
(5) Cryptocurrency theme-oriented
Persist in posting cryptocurrency-related content, reasonably use cryptocurrency keywords, and prioritize discussions on hot projects.
(6) Participation in the recommendation program
Earn extra points by recommending new users.