Why Advice from New Cryptocurrency Project KOLs Fails: The Truth Revealed by Data on 40 Tokens in 2025

In the cryptocurrency industry, influential opinion leaders known as KOLs constantly present formulas for successful token launches. Factors such as 100,000 followers, high Twitter engagement, attracting famous VC funding, and low initial circulation—these elements are all touted as guarantees of a new project’s success. However, recent analysis by Simplicity Group of 50,000 data points collected from 40 major token issuances in 2025 reveals that these strategies widely promoted by KOLs are actually almost unrelated to the actual performance of tokens.

Four Strategies Emphasized by KOLs, Verified by Data

Engagement Metrics Do Not Correlate with Price Performance

Within the crypto community, Twitter likes, retweets, and comments are viewed as key indicators of project success. But the research results are shocking. According to regression analysis by Simplicity Group, the correlation coefficient between engagement metrics and weekly price performance is only 0.038. This indicates almost no correlation. Even likes, comments, and reposts show a weak negative correlation with price performance, meaning higher engagement sometimes leads to poorer results.

Projects like GoPlus, SonicSVM, and RedStone, despite consistently posting content, did not see user engagement meet expectations. Spending thousands of dollars to buy bot engagement and plan complex activities as recommended by KOLs ultimately results in “meaningless” capital exhaustion.

The Myth of Low Circulation Is Statistically Invalid

In the crypto community, there is a tendency to chase “low circulation, high FDV (Fully Diluted Valuation)” projects. The expectation is that artificially creating scarcity by circulating only a small portion of tokens will cause prices to skyrocket. But data refutes this. The initial circulation ratio relative to total supply has no statistically significant correlation with price performance.

The truly important variable is the actual dollar value of the initial market cap. The R² value is 0.273, and the adjusted R² is 0.234, indicating that for each unit increase in initial market cap (IMC), the one-week return decreases by approximately 1.37 units. Simply put, every 2.7-fold increase in initial market cap correlates with about a 1.56% decrease in first-month stock returns. The key factor is not the proportion of tokens unlocked but the total dollar amount flowing into the market.

VC Funding Size Is Not a Guarantee of Success

News that “a16z raised $100 million!” is widely seen among KOLs as a strong buy signal. But the reality is cold. The correlation coefficient between funding size and one-week return is only 0.1186 (p-value 0.46), and with one-month return is 0.2 (p-value 0.22), both statistically insignificant.

The amount a project raises has virtually no causal relationship with token performance. Raising more funds results in higher valuation, which in turn means greater selling pressure. Additional capital does not automatically translate into better token economics or a stronger community. Securing $100 million does not necessarily guarantee better performance than raising $10 million.

KOLs’ Mistake in Missing the Timing of Overhyped Announcements

The common wisdom is to release the most important news during the launch week to maximize FOMO and attract attention. But data shows the opposite. When a project actually launches, user engagement drops sharply. People turn their attention to the next airdrop, and carefully prepared content is ignored.

Successful projects build awareness before the launch, not during. Pre-launch interest attracts actual buyers, while interest during launch only draws “passing speculators.” User engagement peaks just before TGE (Token Generation Event) preview releases and then plummets afterward.

The True Causes of Token Success: Product Strength and Rational Valuation

So, what are the core factors behind successful tokens? The truth revealed by data is surprisingly simple.

Naturally Generated Product Content

Products with genuine utility like Bubblemaps (on-chain survey features) or Kaito (Web3 narrative tracking) outperform meme-centric accounts by far. These generate alpha content organically, ensuring continuous user engagement.

Maintaining Trading Volume After Initial Hype

Tokens that sustain trading volume after initial promotion tend to perform significantly better. Spearman rank correlation coefficient is -0.356 (p=0.014), indicating that tokens with larger drops in trading volume after launch tend to perform worse. The average price performance of the top quartile in trading volume retention one month after issuance is markedly higher.

Reasonable Initial Market Cap

The most powerful predictor of success. The correlation coefficient is -1.56, statistically significant. Listing with a rational valuation opens the door to growth potential. Conversely, starting with a market cap over $1 billion is akin to directly opposing market trends.

Authentic Communication That Fits the Product

Powerloom raised $5.2 million but maintained an overly cynical tone, leading to a 77% drop in the first week and a 95% decline afterward. In contrast, Walrus communicated with genuine humor, resulting in a 357% increase after TGE. Hyperlane focused on realistic updates, soaring 533% in the first week.

Why Does the Crypto Community Spread Misinformation?

This discrepancy is less malicious than structural. Crypto Twitter (CT) operates on an algorithm that prioritizes engagement over accuracy. A post titled “10 Ways to 100x Your Token Launch” receives far more retweets than one showing “what actual data reveals.”

Many KOLs prefer to gather followers with “tailored” prescriptions rather than challenging advice. Critically, most KOLs on CT have never actually issued tokens themselves—they review games they’ve never played.

In contrast, projects like Story Protocol, which have actually launched products, consistently perform well regardless of follower count. Quai Network focused on explaining its unique blockchain consensus model, and despite an average of only 24,000 page views during TGE, QUAI surged 150% in the first week. This was driven not by millions of followers but by genuine interest in innovation.

Meanwhile, projects that poured money into challenge platforms and participatory marketing failed because no one understood what they were building, causing tokens to plummet. Zora, which failed to disclose tokenomics details in time, saw a 50% drop just one week after TGE.

The Laws of Success Revealed by Data

What do successful projects actually do?

• Create products that people genuinely want to use
• Set rational valuations at launch
• Communicate authentically with their audience
• Focus on real metrics, not likes

This doesn’t mean KOL advice is always wrong. But when the incentive structure of the crypto community rewards attention more than solid data, useful information gets drowned out in noise. True innovation comes not from superficial advice tailored to Twitter algorithms but from quietly building something useful and releasing it wisely.