Move over the endless X threads and VC endorsements. A deep dive into the token launch dynamics by Simplicity Group shows that token debuts are more about cold, hard fundamentals and less about hype and marketing.
The firm analyzed over 50,000 data points related to 40 crypto token launches in the first four months of the year to derive following conclusions:
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The popular notion in the crypto community is that increased activity on social media translates to a successful token launch. But Simplicity Group found no statistical relationship between social media engagements, particularly replies, post and likes on X (formerly Twitter) and price performance of the token in one-week after the launch.
Infact, research points to negative correlation between interactions and returns one-week and one-month after the launch – indicating that the more replies, reposts and likes the project had, the worst its price performed. “This is statistically insignificant correlation, and not caustion, yet something to note,” the report said.
However, projects with more engagement ahead of the token generation event (TGE), as a data set of its own, had stronger one-month performance likely due to broader base of awareness.
The research analyzed the correlation between the initial market cap (IMC) and initial circulating supply (referred to as initial float) and the price performance one-week and one-month after the TGE.
It found a strong negative correlation between a token’s IMC and its price performance. “For every 2.7x increase in IMC, there’s an approximately 1.37% drop in 1-week returns and a 1.56% drop in 1-month returns,” the report said.
The report further noted that a lower IMC usually translates into a price pump over the first week, with the strength lasting for at least a month.
Meanwhile, initial circulating supply is irrelevant for predicting one-week price performance, the report revealed, implying that the total dollar value of the initial float matters more than the percentage of supply unlocked at the launch.
The report collected volumes on TGE, one week after the launch and one month following the launch and analyzed the correlation with the price performance.
Initially the two appeared uncorrelated, but Spearman’s rank correlation showed that tokens that experienced a drop in volume tended to perform worse in price terms.
“In simpler terms, while it seemed that performance is not linearly tied to volume, tokens with higher volume retention tend [to] perform better, even if the relationship between the numerical values isn’t linear,” the report noted.
Volume retention, calculated as the ratio, refers to how much of the volume is sustained one month following the TGE.
Lastly, the report scrutinized a popular belief that a well-funded project backed by big VCs is destined for success. The report, however, noted that, “raising more money does not mean you will have a better token, as the extra benefits of more cash do not, statistically speaking, outweigh the costs.”
The study found little to no statistically significant relationship between the amount of money raised by a project and its token’s price performance.
Simplicity Group’s quantitive analysis showed that product-driven content and genuine user engagement far outweigh generic marketing efforts in driving sustainable token success.
The study cited Bubblemaps and Kaito as projects that organically generate content related to their core product functionality, demonstrating consistent engagement and positive price performance.
In contrast, those relying on heavy memes, promotional campaigns and generic calls-to-action have seen a sharp drop in engagement immediately following the TGE, leading to weaker price outcomes. The report also stressed the need for a consistent and authentic tone in all communications, aligning with the projects overall brand target, use case and target audience.
Lastly, it highlighted the critical role of transparency and acessible technical updates in building credibility.
Disclaimer: Parts of this article were generated with the assistance from AI tools and reviewed by our editorial team to ensure accuracy and adherence to our standards. For more information, see .
