The "hierarchical differentiation" of the KOL ecosystem is accelerating.

Written by: Haotian

Regarding the airdrop from @humafinance to Kaito Yaper, the underlying mechanisms are much deeper than they appear on the surface. Here are three points:

1) The transition from "interaction-based" to "algorithm-based" in the airdrop era. In the past, airdrops relied on "diligence"—opening multiple wallets, increasing interactions, and boosting TVL. Now, we have directly entered an era where "algorithmic weight" and Mindshare are the focus.

Platforms like @KaitoAI and @cookiedotfun essentially create a "digital profile" for each KOL, quantifying content value, audience quality, interaction efficiency, and other influence dimensions through machine learning.

To some extent, this upgrades the KOL selection mechanism, which originally depended on "insider relationships" and "subjective judgment," to a precise, AI data-driven approach.

However, initial algorithm assessments can be unsatisfactory. For example, small-scale collusion can occur through mutual liking groups, follower boosting, and comment exchanges, leading to a short-term influx of airdrop studios eager to seize opportunities.

But don't forget that algorithms can be continuously optimized. Paying attention to IP and asset relevance can help avoid being targeted by "witches," but in the case of algorithmic assessments, especially in "black box" situations, the probability of being targeted will only increase. Treating this as a "business strategy for airdrops" requires caution.

2) The "hierarchical differentiation" of the platform KOL ecosystem will accelerate. To be honest, top KOLs already possess Alpha research capabilities and have early access to quality projects, allowing them to monetize their influence through consulting, investment, and on-chain finance.

As a result, these big influencers tend to be more "aloof," posting infrequently and interacting cautiously, which may lead them to be classified as "inactive users" by algorithms. In contrast, some mid-tier and lower-tier KOLs frequently retweet, comment, and interact daily, scoring high in algorithmic activity ratings.

This actually exposes a core bug in the current algorithmic assessment—mistaking "quantity" for "quality" and "frequency" for "value." In the short term, this will indeed bring a wave of benefits to KOLs willing to frequently promote projects.

However, ultimately, algorithms must rely on objective influence assessments to succeed. As algorithms continue to optimize, "interaction frequency" will inevitably give way to "content value" weight; otherwise, top KOLs and high-quality projects will leave, which is something platform operators controlling the algorithmic black box definitely do not want to see. The key is how to balance content value and interaction frequency to avoid severe differentiation of platform KOL resources.

3) The "hidden inflation" of marketing costs for project parties has already begun. On the surface, moving from hiring agencies to package KOL resources to directly using platforms like Kaito for precise targeting seems to eliminate intermediaries. But what is the reality? Project parties must pay booth fees to participate in this "algorithm arms race," and as competition for bidding positions intensifies, hidden costs will only rise.

What's more concerning is that algorithms overly rely on quantitative metrics—like the number of interactions from Smart Followers—while neglecting truly valuable elements such as content depth, audience quality, and brand compatibility. The issues arising from algorithmic bias are evident:

First, marketing ROI declines—airdropping to accounts with mismatched influence value will certainly yield lower conversion results than expected; second, brand reputation risks—overemphasizing interaction quantity rather than content quality could damage the market recognition that project parties have worked hard to establish.

Of course, this is also a dynamic game process. Algorithm models will continuously optimize, and project parties can intervene for adjustments. Ultimately, it must return to the mutual matching of brand value and user value for the business of algorithm platforms like Kaito and Cookie to truly grow and strengthen.

Note: Personally, I acquire Yap points in a very laid-back manner. In the past week, I've noticeably felt that valuable content has been weighted more heavily, resulting in a higher ranking. Platforms like this AI algorithm platform play a significant role in the allocation of "ecological niches" in the attention economy's Mindshare.

However, it's best to avoid a monopoly, so supporting more platforms similar to Cookie to join the competition is very necessary.

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