The truth that crypto KOLs won’t tell you: Four major illusions and data falsifications of new project launches

Author: rosie , Crypto KOL

Compiled by: Felix, PANews

Crypto Twitter (CT) always likes to tell you how to launch a token: accumulate 100k followers first, increase engagement through tasks, raise funds from Tier 1 VCs, control the circulating supply at 2% at launch, and maximize hype during the week of the Token Generation Event (TGE).

Here’s the thing: it’s all bullshit.

Simplicity Group recently released a research report that analyzed 50,000 data points from 40 major token issuances in 2025. The results showed that the traditional methods promoted on CT do not work in actual token issuance.

The Lie About Engagement

Everyone (even me) is obsessed with Twitter metrics. Likes, retweets, replies, impressions — all those vanity metrics. Projects spend thousands of dollars on engagement farming, tasking platforms, and buying followers.

Correlation with price performance over the week: Almost zero.

Regression analysis by Simplicity Group shows that the correlation coefficient between participation metrics and price performance is only 0.038. In short: participation explains almost nothing about token success.

Likes, comments, and reposts actually have a slight negative correlation with price performance. This means that projects with higher engagement sometimes perform worse. GoPlus, SonicSVM, and RedStone are constantly publishing content, but their user engagement is not proportional to their user base.

The only metric that shows a positive correlation is surprisingly the number of retweets in the week before the post. The p-value is 0.094, barely statistically significant, but even so, the correlation is weak.

Therefore, when you spend money to buy water armies and carefully plan complex task activities, you are actually just burning money "meaninglessly".

The low circulation myth

CT is obsessed with "low circulation, high FDV" projects. The idea is to issue a token with a very small circulating supply, create artificial scarcity, and then watch the price soar.

But it turned out to be wrong again.

Initial circulation as a percentage of total supply has no correlation with price performance. Studies have shown that it does not have any statistically significant correlation at all.

What really matters is: the USD value of the initial market cap.

The R² is 0.273 and the adjusted R² is 0.234, and the relationship between the two is very clear: for every 1 unit increase in the initial market value (IMC), the return rate after one week will decrease by about 1.37 units.

In short: for every 2.7x increase in initial market cap, price performance in the first month drops by about 1.56%. This relationship is so strong that it almost seems causal.

Lesson: It’s not the percentage of tokens unlocked that matters, but the total dollar value entering the market.

The illusion of VC support

“Wow, they raised $100 million from a16z, this is going to skyrocket!”

Narrator: The results did not skyrocket.

The correlation between the amount of financing and the one-week return rate is 0.1186, with a p-value of 0.46. The correlation between the amount of financing and the one-month return rate is 0.2, with a p-value of 0.22.

Neither is statistically significant. There is virtually no relationship between the amount of money a project raises and the performance of its token.

Why? Because more money raised generally means a higher valuation, which means more selling pressure to overcome. Additional funds do not magically translate into a better token.

Yet CT sees financing announcements as buy signals. This is like judging a restaurant by the rent the owner pays.

Perfect example: projects in the study that raised huge amounts of money did not necessarily perform better than projects that raised more limited amounts. A $100 million round does not guarantee a better token economy or a stronger community than a $10 million round.

The hype timing fallacy

Conventional wisdom holds that the most important news should be saved for launch week to maximize FOMO and grab everyone’s attention when the token goes live.

But the data suggests the opposite is true.

After the project is launched, user engagement will decline. Users will move on to the next project with an airdrop, and your carefully prepared content will be ignored.

Projects that perform consistently well build awareness before launch week, not during it. They understand that pre-launch attention brings real buyers, while launch week attention brings “passers-by.” User engagement peaks before the TGE, when they release a preview of the launch, not after the launch, when everyone has moved on to the next opportunity.

A truly effective method

If Twitter engagement, low liquidity, VC backing, and hype timing don’t matter, then what does?

Actual product effectiveness

Projects that naturally generate content, such as Bubblemaps with its on-chain survey functionality or Kaito with its narrative tracking functionality, outperform meme-focused accounts. Bubblemaps and Kaito have large and sustained user engagement because their products naturally create alpha-full content.

Transaction retention rate

Tokens that maintained trading volume after the initial hype had significantly better price performance. The Spearman rank correlation coefficient was -0.356 (p = 0.014 ) - tokens with larger declines in trading volume tended to have worse price performance. One month after issuance, the top quartile of volume retention had significantly higher median and mean price performance .

Reasonable initial market value

The strongest predictor of success. The correlation is -1.56 and is statistically significant. Go public at a reasonable valuation and you have room to grow. Go public at a market cap of $1 billion or more and you’re going against the grain.

Real communication

A consistent tone that matches the product. Powerloom’s $5.2 million raise was at odds with an overly cynical tone — POWER plummeted 77% in its first week and is down 95% since launch. Meanwhile, Walrus tweeted with genuine humor, and a month later the token offering (TGE) price was up 357%. Hyperlane stuck to a matter-of-fact update and surged 533% in its first week.

Why did CT go wrong?

This disconnect is not malicious, it is structural.

CT rewards engagement, not accuracy. A post about “10 ways to 100x your token launch” gets more retweets than “what the data actually shows”.

KOLs accumulate fans by "catering" to projects instead of challenging them. Telling users that their engagement farming is meaningless and will not bring returns.

In addition, most KOLs on CT have never actually issued a token. They are just reviewing a game they have never played. And projects like Story Protocol that have actually launched a product continue to perform well, regardless of the number of Twitter followers.

True Meta

Here’s what successful projects actually do (based on data):

• Focus on building products people want to use
• Reasonable pricing at token launch
• Communicate sincerely with your audience
• Measure what really matters, not the number of likes

This is absolutely revolutionary stuff.

Take Quai Network for example - they focus on technical explanations and educational posts about their unique blockchain consensus model. During the TGE, the average pageview was about 24k. QUAI rose 150% in the first week after launch. This is not because they have millions of followers, but because they have truly sparked interest in their innovation.

In contrast, projects that burned money on task platforms and participatory marketing saw their tokens plummet because no one really understood or cared about what they were building.

The irony is that while everyone is catering to the Twitter algorithm, the projects that are really succeeding are those that are quietly building useful things and releasing them wisely.

Case study: Zora’s failure to disclose token economics details in a timely manner led to a 50% plunge a week after its TGE. Meanwhile, projects that are transparent in their approach and focus on product-driven content have consistently outperformed.

CT doesn’t mean to lie. But when incentives reward popular opinions rather than hard data, useful information gets lost in the noise.

Related reading: The influence economy of crypto Twitter: How a small number of accounts control the narrative