Data: 90% of Crypto Protocols Generate Revenue, But Less Than 1% Disclose Market Maker Terms

marsbitPublicado em 2026-04-15Última atualização em 2026-04-15

Resumo

Survey of 150 major crypto protocols reveals that while 91% generate on-chain revenue, only 8% publish investor reports, and less than 1% disclose market maker agreements. The data indicates a significant communication gap rather than a lack of available information, as third-party platforms cover 72% of protocols. DeFi protocols, particularly DEXs and lending platforms, lead in transparency, while L1 and infrastructure projects lag despite larger market capitalizations. Only 13 protocols have adopted the Token Transparency Framework since its introduction in June 2025. Additionally, 38% of protocols feature active value accumulation mechanisms, which correlate with approximately 19% higher annual returns compared to governance-only tokens. The findings highlight a structural disconnect between institutional investor expectations and current disclosure practices in the crypto industry.

Author: Novora

Compiled by: Deep Tide TechFlow

Deep Tide Intro: Among 150 leading protocols, 91% generate on-chain revenue, but only 8% publish investor reports, and less than 1% disclose market maker terms. The data is all on-chain, and third-party platforms also cover it, but protocols simply aren't packaging it for institutional view. This is not a data availability issue, but more of a communication gap.

Disclosure Rate

We evaluated 13 disclosure metrics across 150+ protocols. The gap between what traditional markets require for disclosure and what crypto protocols voluntarily provide is structural, not accidental.

Less than 1% of protocols disclose market maker terms. In traditional stock markets, market maker agreements are standard disclosure items filed with exchanges. In crypto, Meteora was the only protocol in our entire 150+ dataset that publicly disclosed information about its market making arrangements, via its 2025 Annual Token Holder Report.

Third-Party Data Coverage

We evaluated 5 major data platforms. Coverage reflects whether each protocol has a dedicated profile containing meaningful data beyond basic price information.

72% of protocols are covered by 4 or more platforms. Third-party data infrastructure has matured significantly. The data exists. The issue is not data availability, but that protocols are not leveraging this data in structured investor communications.

The Transparency Paradox

Revenue exists on-chain. Reports exist nowhere. This chart shows the disconnect between data availability and investor communication.

91% of protocols generate trackable revenue. 8% publish token holder reports. The data is there. It's on-chain, indexed by third-party platforms, and publicly verifiable. But fewer than one in ten protocols package this data into a format usable by institutional investors. This is the investor relations gap defining the industry.

Industry Breakdown

Disclosure practices vary dramatically by industry. DeFi protocols, particularly DEXs and lending, lead in transparency. L1 and infrastructure protocols, despite larger market caps, lag behind.

Token Transparency Framework

Blockworks launched the Token Transparency Framework (TTF) in June 2025, filed jointly with Jito to the SEC. 13 protocols have filed. Here's who they are and what this means.

TTF adoption is at 9%, up from 0% in June 2025. The 13 filers are heavily skewed towards Solana (6/13) and revenue-generating DeFi protocols. Zero L1s, zero L2s, zero infrastructure protocols have filed. The framework was submitted to the SEC with bipartisan support from Pantera, Theia, and L1D. But adoption is still growing slowly.

Active Value Accrual

38% of protocols have some form of active value accrual: a mechanism to return economic value to token holders, beyond just governance rights. But "value accrual" is not one thing. We identified six different models in the dataset.

The alpha is not in the mechanism itself. It's in the revenue. Any active accrual model outperformed governance-only tokens by approximately 19 percentage points on a 1-year return basis. But within the active group, daily revenue size was the differentiating factor. Governance-only tokens averaged a -51% return, while active accrual tokens averaged -32% over the same period. The mechanism itself matters less than the fact that a mechanism exists.

Key Findings

Six patterns emerging from evaluating all 15 metrics across 150+ protocols.

Six Numbers on the State of Crypto Investor Relations

The gap between institutional investor expectations and what crypto protocols provide, quantified.

Protocol Index

Each protocol evaluated in this report. Sorted alphabetically. ✓ = Disclosed/Exists. ✗ = Not Disclosed/Missing. Hover on mobile to view full row.

150+ protocols evaluated on 18 total metrics (13 disclosure + 5 platform coverage). This index represents the most comprehensive assessment of crypto investor relations practices to date. The full dataset is maintained in the Novora Investor Relations Benchmark Database, updated quarterly.

Click here for full content

Perguntas relacionadas

QWhat percentage of the top 150 crypto protocols generate on-chain revenue according to the article?

A91% of the top protocols generate on-chain revenue.

QHow many protocols in the dataset publicly disclosed their market maker arrangements?

AOnly one protocol, Meteora, publicly disclosed its market maker arrangements.

QWhat is the adoption rate of the Token Transparency Framework (TTF) mentioned in the report?

AThe adoption rate of the Token Transparency Framework is 9%.

QWhat percentage of protocols release token holder reports, as stated in the article?

AOnly 8% of protocols release token holder reports.

QWhat is the performance difference in 1-year returns between governance-only tokens and tokens with active value accumulation mechanisms?

ATokens with active value accumulation mechanisms outperformed governance-only tokens by approximately 19 percentage points on a 1-year return basis.

Leituras Relacionadas

When Doing Cryptocurrency Payment, the First Thing is Licenses, What is the Second?

When launching a crypto payment business, obtaining the necessary licenses is the crucial first step. However, the second, and arguably more critical, step is designing a comprehensive operational framework that forms a coherent business loop. This loop must be clearly understood and executable by all stakeholders: banks, payment partners, exchanges, on-chain analytics providers, regulators, and your internal team. Many projects mistakenly believe a single license permits all operations. Licenses merely grant entry; they don't define how the specific business functions. The real challenge lies in detailing every aspect of the workflow. This involves clarifying the customer base, the flow of fiat and crypto assets, the settlement process, and establishing clear lines of responsibility for risks like AML compliance, sanctions screening, chargebacks, and regulatory inquiries. A robust framework must answer seven core questions: Who are the clients and merchants? Who collects fiat and crypto? Who handles conversion and custody? And who is ultimately accountable for compliance and risk management? Projects often fail not from a lack of licensing, but during due diligence when they cannot convincingly explain these operational details. Therefore, beyond securing licenses, the priority must be constructing a closed-loop system. This system ensures the business model is transparent, risks are managed, responsibilities are delineated, contracts are aligned, and the entire process is comprehensible to partners and regulators. The true competitive edge in crypto payments lies not in acquiring a license quickly, but in integrating licensing, banking, compliance, and operations into a sustainable and executable whole.

marsbitHá 5m

When Doing Cryptocurrency Payment, the First Thing is Licenses, What is the Second?

marsbitHá 5m

Arthur Hayes Analysis: AI Bubble Nears Burst, Crypto Market Faces Short-Term Pressure

Arthur Hayes argues that the current AI market is a bubble poised to burst, which will exert downward pressure on the crypto market in the near term. The core trigger is rising oil prices due to the US-Iran conflict and a blockade of the Strait of Hormuz. Higher energy costs directly increase the operational expenses of AI data centers, squeezing profit margins for companies like Google, Anthropic, and OpenAI. Hayes predicts that persistent inflation from high oil prices will force Trump, in a bid to win the November election, to turn public sentiment against the AI industry. He may propose regulations and taxes on data centers and AI companies to appeal to voters concerned about costs and job displacement. Such political rhetoric could shatter market confidence. Furthermore, the market is unlikely to healthily absorb the massive concurrent IPOs of SpaceX, Anthropic, and OpenAI, which together seek valuations in the trillions. The combination of soaring energy costs, overwhelming equity supply, and negative political pressure will puncture the AI bubble. Hayes notes that nearly all new USD liquidity since 2022 has flowed into AI, leaving crypto like Bitcoin behind. When the AI bubble bursts, liquidity will contract sharply, pulling down all risk assets, including cryptocurrencies. In response, Hayes's fund, Maelstrom, has sold all AI-related stocks and non-core cryptocurrencies. It maintains core positions in Bitcoin and Ethereum while increasing exposure to energy sector equities, betting on rising oil and gas prices. He expects Bitcoin to bottom after the AI-led market decline, before rallying again with future monetary easing.

Foresight NewsHá 18m

Arthur Hayes Analysis: AI Bubble Nears Burst, Crypto Market Faces Short-Term Pressure

Foresight NewsHá 18m

To C, To B, and the Next Big Thing Called To A

After To C and To B, the Next Wave is To A: Serving AI Agents In a recent quarterly earnings call, Meituan's Wang Xing introduced a new concept: To A (To Agent), signifying that future business services will increasingly target AI Agents as primary clients, not just consumers or merchants. This shift implies that internet giants must now consider how to make their services more appealing for AI Agents to recommend, fundamentally altering traditional distribution logic. This "To A era" is prompting an unusual trend of alliances among major tech companies. Unlike previous competitive battles, firms like Meituan, Tencent, JD.com, Huawei, OPPO, and OpenAI are rapidly forming partnerships. The reason is strategic: as AI Agents become the primary user interface, handling tasks from a single command (e.g., "Book a Japanese restaurant for tomorrow"), the risk for platforms is being bypassed entirely. Companies are positioning themselves within this new value chain. Three primary strategies are emerging: 1. **Super-Entry Points + Service Providers:** Platforms like Tencent's Yuanbao, WeChat, and ChatGPT aim to be the first-stop Agent, integrating various services (food delivery, shopping, travel) from partners like Meituan and JD.com. 2. **Apps as Callable Services:** Companies like Meituan, JD.com, and Uber are ensuring their core services remain accessible and callable by external Agents, shifting from front-end apps to back-end capabilities. 3. **System-Level Agent Entry Points:** Smartphone makers (Huawei, Honor, OPPO) are leveraging their OS-level AI assistants to control the initial user command, redistributing it to relevant service apps. While alliances offer mutual benefit—entry points gain service capabilities, and service providers gain traffic—inherent conflicts of interest exist. A dominant Agent platform could eventually attempt to connect directly with suppliers (restaurants, hotels), bypassing current aggregators like Meituan or Ctrip. Other unresolved challenges include the potential for Agent recommendations to become a new form of paid ranking and unclear accountability for faulty recommendations. The current rush to form alliances is a defensive move by service providers to secure their position before the landscape solidifies. In this To A-driven restructuring, the greatest risk is not losing the race but failing to hear the starting gun.

marsbitHá 27m

To C, To B, and the Next Big Thing Called To A

marsbitHá 27m

The More Lifelike the Robot, the More Terrifying? Unveiling the 'Uncanny Valley Effect' in the Era of Humanoid Robots

As humanoid robots become increasingly lifelike, they confront a significant psychological barrier known as the "Uncanny Valley Effect," a concept proposed by Japanese roboticist Masahiro Mori in 1970. This phenomenon describes a dip in human comfort and acceptance when robots appear almost, but not perfectly, human. Minor imperfections in facial expressions, eye movements, or skin texture trigger a subconscious sense of unease, as the brain detects something trying, yet failing, to mimic a person. Examples range from the controversial human-like robot Sophia to animated characters in films like *The Polar Express*. The effect poses a key design challenge for robotics companies. Some, like Boston Dynamics, avoid it entirely by creating highly capable but visibly mechanical robots. Others, like Hanson Robotics, push for greater human likeness despite the risk. For consumer robots, especially in homes, most manufacturers opt for stylized or clearly mechanical designs to ensure broader acceptance. While the Uncanny Valley remains a powerful force, its impact may diminish over time through technological advancements that achieve near-perfect realism or through generational familiarity as people grow accustomed to interacting with humanoid machines. Ultimately, navigating this psychological frontier requires as much understanding of human perception as of robotics technology itself.

marsbitHá 28m

The More Lifelike the Robot, the More Terrifying? Unveiling the 'Uncanny Valley Effect' in the Era of Humanoid Robots

marsbitHá 28m

Over $31 Million Stolen from Humanity, Is the Team Behind It Paving the Way for a New Project?

The article reports a major security incident involving Humanity Protocol (H), resulting in over $31 million stolen. The team attributes the hack to a private key leak from a Humanity Foundation member, leading to a rapid sale of H tokens and a 90% price drop. However, prominent on-chain investigator ZachXBT suggests the event might be an "exit scam" orchestrated by the team, rather than an external hack. This suspicion is fueled by the team's controversial history, including past management failures, legal issues, and previous scandals like outsourced technology and problematic airdrops. Further investigation reveals that the core team behind Humanity is already involved with a new project called "Everything," which recently secured funding. This has led to community speculation that the alleged hack is a deliberate scheme to abandon the H project while shifting focus and resources to their new venture, leaving investors to bear the losses. The article questions whether this is a genuine security failure or a premeditated "rug pull" strategy.

Odaily星球日报Há 1h

Over $31 Million Stolen from Humanity, Is the Team Behind It Paving the Way for a New Project?

Odaily星球日报Há 1h

Trading

Spot
Futuros
活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow