Forward the Original Title ‘链上数据产品洞察：Web3时代的数据分析革命’

Introduction

In today’s rapidly evolving blockchain landscape, on-chain data has become a core asset, with its ecological importance growing by the day. From token transactions to NFT minting, every detail of on-chain activity is shaping the landscape of value flow. In this data-driven era, on-chain data is not just a collection of numbers but a true reflection of market dynamics, user behavior, and the overall health of the blockchain ecosystem.

Marketing teaches us that consumer behavior analysis has profound implications for future market trends. Similarly, in the world of blockchain, in-depth analysis and insights into user behavior hold immeasurable value for market participants. Nansen, Lookonchain, and Dune Analytics, as leading projects in crypto data analysis, not only provide users with in-depth on-chain data analysis but also form an integral part of blockchain development. This study will explore the characteristics of these three platforms and their significance for the development of blockchain technology.

Importance of on-chain data analysis

On-chain data reflects user behavior. In the world of blockchain, on-chain data can represent individuals, institutions, exchanges, market makers, and all other entities participating in on-chain activities. On-chain data analysis can provide insights into market trends and user behavior, discover potential opportunities and risks, improve operational efficiency and reduce costs, support decision-making and strategic planning, as well as strengthen security and risk management. Through in-depth analysis of on-chain data, both retail investors and institutions can benefit in several ways:

1. Provide data support for decision-making: On-chain data provides investors and project parties with an objective perspective, helping them better understand the actual market situation and make wise investment decisions.
2. Optimize market strategies: In-depth analysis of on-chain data helps project parties and traders understand market needs and changes, thereby adjusting market strategies.
3. Improve operational efficiency: Optimize resource allocation and processes by identifying bottlenecks and issues in operations.
4. Promote innovation and R&D: Provide valuable feedback to project parties to help them understand user needs and keep pace with market and user needs.
5. Improve transparency and trust: On-chain data provides an open and transparent platform for all participants in the decentralized ecosystem, enhancing system trust. Discover potential opportunities and risks: Help discover market opportunities and potential risks and reduce risks.
6. Strengthen security and risk control: monitor and analyze data on the chain in real time, detect abnormal behaviors and risk events in a timely manner, and prevent and respond to them.

Source: Bing Ventures

Typical functions of Web3 data tools Nansen, Dune Analytics and LookOnChain, as leaders in this field, have their own characteristics and provide users with unique and in-depth insights. An in-depth analysis of these tools not only reveals their respective strengths and limitations, but also explores future trends in the data market and their impact on investors.

Nansen — a pioneer in on-chain behavioral analysis

Source: Nansen

Nansen provides an in-depth understanding of the crypto market through behavioral analysis of over 120 million wallet addresses. It mainly focuses on token holdings, exchange inflows and outflows, and smart contract dynamics. Through its complex label system and early warning system, Nansen enables users to quickly identify market trends and capture investment opportunities in a timely manner.

In-depth analysis at the token level

Nansen’s analysis at the token level covers multiple dimensions, including Smart Money’s position changes, exchange capital flows, and the overall market performance of the token. This comprehensive perspective allows investors to understand market dynamics from multiple perspectives and make more accurate investment decisions.

Source: Nansen

Actual operation

Source: Nansen

Start from the market level, look at the trading situation of smart money that day, and infer their trading thinking (large amounts of buying: potential speculation opportunities; large amounts of selling: potential selling opportunities), so as to explore potential projects for investment. Unfamiliar items arise that allow for more in-depth study.

Source: Nansen

In the world of cryptocurrency and blockchain, smart money operations are often seen as one of the indicators of market trends. Different smart money groups, such as Flash Boys, funds and other large holders, have their unique trading patterns and strategies. A deep understanding of these patterns and strategies can provide investors with valuable trading signals and market insights.

Observations on Flash Boys Trading

Features

Flash Boys usually pursue short-term profits, and their trading strategies are often based on technical analysis and market sentiment rather than long-term fundamental analysis.

trading signals

Observing Flash Boys’ trades can provide clues about short-term market trends. For example, if Flash Boys purchases a large amount of a certain token, this could mean that the token has the potential to rise in the short term.

Risk

Since Flash Boys’ strategies are often based on short-term trends, trading with them may carry higher risks. Investors need to ensure that their trading strategy matches their risk tolerance.

Observations on Fund Trading

Features

Funds and other large holders often adopt more conservative and long-term investment strategies. Their trading decisions or biases are based on in-depth market research and fundamental analysis.

Trading signals

Observing a fund trading can provide clues about mid- to long-term market trends. For example, if multiple large funds start accumulating holdings of a token, this could mean that the token has the potential for long-term growth.

Strategy Reference

Fund investment strategies tend to be more robust and systematic. By analyzing the trading patterns of funds, investors can learn and refer to their investment strategies to optimize their investment portfolios. But Crypto fund investments are often accompanied by regular unlocking of tokens. Therefore, the fund’s positions and transfers cannot reflect the market’s judgment on the trend of a specific currency to a certain extent. Investors need to be more cautious.

Smart Contract and Liquidity Provider Analysis

Nansen shows users key indicators such as annualized yield (APY) by tracking the trading pairs of popular contracts and liquidity providers (LPs). This data is crucial for assessing the potential value and risks of DeFi projects.

Source: Nansen

Labeling system and early warning mechanism Nansen’s labeling system and early warning mechanism provide timely feedback on market dynamics. By tracking specific tags and wallet addresses, users can obtain important market information in a timely manner and quickly adjust investment strategies.

Source: Nansen

Actual operation

Source: Nansen

Nansen AI’s early warning system provides cryptocurrency investors and project parties with a powerful tool to help them capture market dynamics, manage risks and optimize strategies in a timely manner.

1. Multi-chain support

Wide coverage - Support for multiple public chain networks means investors can track the dynamics of multiple markets and gain a more comprehensive market perspective.

Flexibility - Whether it is TOKEN or NFT, users can choose and track according to their own needs, providing great flexibility.

1. Custom alert

Smart money tracking - Users can add the wallet address of smart money and keep abreast of its transaction dynamics to capture market opportunities or avoid risks.

Tag indicator filtering - Through the numerous tag indicators provided by @nansen_ai, users can set warning conditions more accurately to ensure the relevance and accuracy of warnings.

Amount filter - Set early warnings based on the transaction amount to help users capture large transactions and important market trends in a timely manner.

1. Notification

Source: Nansen, Telegram

Multi-platform access - Early warnings can be connected to TG (Telegram) and DC (Discord) to ensure that users can receive timely warning information on multiple platforms.

User friendliness - Simple and easy to use Users can easily customize and set warning conditions without complicated operations.

Flexibility - The early warning system provides strong selectivity and operability, and users can flexibly configure it according to their own needs.

Generally speaking, the current services provided by Nansen’s AI system are relatively similar to Bot, which is based on tracking of specific address/token related information input in advance. The user experience also adopts a push form based on Telegram similar to Bot. At present, the degree of AI participation in intelligent analysis is relatively low, mainly related push based on on-chain activities. From the current perspective, it still lacks some innovation and competitiveness. Nansen may develop efforts in related products in the future.

Dune Analytics - A Data-Driven Market Insight Lens

Dune Analytics provides powerful data analysis capabilities based on SQL, covering multiple aspects of the cryptocurrency and DeFi fields. Its community-driven model and open data access policy make it an extremely dynamic analytics platform.

Source: Dune

Community Sharing and Collaboration

Dune’s community culture encourages data sharing and collaboration, providing users with a continuously evolving data analysis environment. Users can easily access and modify others’ dashboards, creating new perspectives to adapt to market changes.

Robust Customization Features

Dune’s customization features allow users to adjust data presentation according to their individual needs. This flexibility is a major advantage of Dune, making it an adaptable tool, especially for advanced users with specific data requirements.

Additionally, the comprehensiveness of Dune Analytics is another key reason for its popularity. It supports data analysis for multiple public chains, providing users with a comprehensive market perspective. Regardless of the project or field users are interested in, they can find detailed data and in-depth analysis on Dune.

Operational Efficiency

Dune Analytics demonstrates its powerful features and user-friendly design in terms of operational efficiency.

Flexibility of Charts - Dune allows users to zoom in, go full screen, and select any part of the chart, providing them with a highly customizable experience to view and analyze data according to their needs.

Fork Functionality - Through the Fork function, users can easily copy the entire dataset to their workspace. This design encourages users to explore and experiment while providing a safe environment for them to modify and innovate without affecting the original dataset.

Query and Code Transparency - The Query feature allows users to view the implementation code of the dataset, increasing transparency and enabling experienced users to understand the source and processing of data in depth.

Search and Sequencing Functionality - Dune’s search function allows users to quickly find the project information they need and sequence it by popularity, bookmarks, and publication date. This greatly improves user efficiency, making it easier for them to find and analyze relevant data.

Code Reuse and Modification - Dune encourages users to copy successful

Source: Dune

Compared to Nansen, Dune’s advantage lies in its customizable design for relevant data. Users can create their desired dashboards based on the open API interface, resulting in greater freedom, flexibility, and combinability. Currently, many projects directly display/disclose their project-related transaction and operational data on Dune, providing users and investors with data references. In contrast, Nansen has formed a “standardized” data format more suitable for institutional and novice users. In the future, Dune can introduce a reward mechanism to incentivize developers who provide dashboards, thereby contributing to the overall development of the Dune ecosystem.

LookOnChain — Intuitive Market Dynamics Tracking

LookOnChain is known for its intuitive Twitter platform and in-depth tracking of whale wallets. It provides users with a unique perspective on market dynamics, especially when it comes to tracking the behavior of large investors.

Source: X

Whale-Oriented Strategy

By following important whale wallets, LookOnChain enables users to quickly grasp market trends. This strategy is particularly suitable for investors who wish to follow market leaders. Through LookOnChain, investors can not only obtain the transaction records of these wallets, but also gain an in-depth understanding of the strategies and motivations behind them. Information like this can be very helpful for investors looking to succeed in the cryptocurrency market. After all, in a market full of variables, having the right information and strategies is the key to success. Therefore, LookOnChain provides investors with a unique opportunity to better understand the market and make informed investment decisions.

Connect with Debank for deeper analysis

LookOnChain provides a more detailed analysis of whale wallets by connecting to DeBank. This in-depth analysis helps users understand the specific strategies and market movements of these large wallets.

The three platforms each show different aspects of on-chain data analysis. Nansen provides users with a comprehensive market perspective with its in-depth wallet behavior analysis and real-time data updates. Dune Analytics provides a collaborative and innovative environment for data analysts and programmers with its powerful customization capabilities and community-sharing culture. LookOnChain enables ordinary users to quickly understand market dynamics in a simple and intuitive way.

Comparative analysis based on multi-dimensional business evaluation model

The data track is one of the essential infrastructures in the Crypto industry. The data analysis platform can not only assist investors in making investment decisions, but also provide assistance for AML and crime tracking. On-chain behavioral analysis is one of the charming points of data-based platforms. The advantage is that potential investment opportunities can be discovered at an early stage. The disadvantage is the risk caused by the uncertainty of investment opportunities. In any case, the information provided by on-chain data should be used as auxiliary information for decision-making. Investors need to accurately implement their operations based on the actual situation and their own judgment.

Overview of Web3 Data Tool Product Monetization Models

Nansen: Institutional Think Tank Model, More Elite

Business profitability: In order to cover all types of users, Nansen has launched three levels of service, which are US$150 (standard level), US$1,500 (VIP level) and US$2,500 (Alpha level) per month. By paying, you can get research reports and project analysis produced by the Nansen team, and have the opportunity to contact Nansen’s professional research analysts.

Source: Nansen

Token economic model: No tokens have been launched yet.

Dune Analytics: Developer Community Model, More Fun

How the business can be monetized: Regular users can access blockchain data, create dashboards, share charts and fork existing queries for free. When they need to run multiple queries at once, skip query execution queues, export results, keep information private, or remove watermarks, they need to upgrade to “Dune Plus” or “Dune Premium,” which are currently priced at $349 and $389 per month respectively. In addition to more powerful basic functions, it also provides more API calls per minute, which helps deepen the connection between enterprises and customers and can transform the platform from an external data provider to part of the customer’s core infrastructure.

Source: Dune

Token economic model: No tokens have been launched yet.

LookOnChain: Model that Follows the Trend, Greater Dissemination Effect

Business profit methods: LookOnChain currently provides free consultation to users within the X platform. The profit methods include paid user groups and exchange-related user recommendations.

Token economic model: No tokens have been launched yet.

From the perspective of traditional multi-dimensional business evaluation model

When comparing these three blockchain data analysis tools, we found that Nansen, Dune Analytics and LookOnChain each showed significant advantages and limitations in different dimensions. Nansen leads in data depth and multi-chain support, Dune Analytics excels in user experience and community-driven content innovation, and LookOnChain has unique advantages in providing intuitive market insights.

Technological innovation

Nansen’s technological innovation is reflected in its in-depth analysis capabilities of more than 120 million wallet addresses. Its core strength lies in its ability to comprehensively analyze token holdings and smart contract activity to provide users with a comprehensive view of the market. However, behind this technical prowess lies an over-reliance on tagged addresses, which can lead to blind spots for emerging or untagged addresses.

Dune Analytics demonstrates its excellent SQL capabilities in data processing. This capability not only puts it at the forefront of data analysis, but also provides the developer community with powerful customization tools that are extremely rare in the market. We are very optimistic about this model.

The innovation of LookOnChain is its ability to directly track the trading dynamics of large investors (whale wallets). This is crucial to quickly capture market trends, especially in the extremely volatile cryptocurrency market.

Market adaptability

Nansen demonstrates broad adaptability to the blockchain ecosystem by supporting multi-chain data analysis. However, this breadth can lead to a fragmented focus that prevents in-depth analysis of specific chains or market segments. We did find this shortcoming of Nansen when using it. It cannot follow up on hot sectors or narrative currency data analysis promptly.

Dune Analytics has quickly adapted to changes in the market through its open community culture and easy-to-use interface design. This flexibility makes it the first choice for those looking for quick responses and deep insights.

LookOnChain leverages the popularity of the Twitter platform to quickly adapt to market dynamics driven by social media. But this also brings the risk of over-reliance on a single platform.

User experience

The label system and early warning system provided by Nansen bring a highly personalized experience to users, but for beginners, the complex user panel still means a complex learning curve.

Dune Analytics received high marks for user experience with its simple SQL interface and rich community content. Its user-friendliness not only appeals to technical users but also provides users from non-technical backgrounds with an easy-to-understand view of the data. It’s a win-win situation.

LookOnChain provides a great experience for non-technical users with its intuitive information presentation and simple user interaction. However, the depth and breadth of its information may sometimes be insufficient to meet the needs of more advanced users.

Business model and profitability

Nansen’s multi-level subscription service reflects its deep understanding of user groups in different markets. This differentiation strategy not only enhances its market coverage, but also brings it a stable revenue stream.

Dune Analytics demonstrates its flexible business model by offering both free services and premium subscription options. This strategy not only ensures the activity of the community, but also brings profit potential to it.

LookOnChain makes full use of its huge Twitter follower base as a supplement to its revenue sources, demonstrating its innovation in business models. However, the sustainability and stability of this model need to be further verified.

On-chain Data Service Evaluation Framework (ODTEF)

In view of the characteristics of the data analysis tools on the Web3 chain, we have further optimized the traditional multi-dimensional business evaluation model to make it more targeted. We will name this optimized model “Onchain Data Tools Analysis Evaluation (ODTEF)”, which pays more attention to the characteristics of blockchain technology and the uniqueness of data tools in the Web3 environment. The main evaluation dimensions include the following aspects:

Decentralization capabilities: Evaluate the degree to which a tool decentralizes the data management and analysis process, including the distributed nature of data storage, processing, and access.

Real-time data tracking and transparency: Whether analytical tools can provide real-time on-chain data monitoring and performance in data transparency and traceability.

Smart contract analysis and interaction capabilities: Examine the tool’s ability to analyze smart contracts, as well as the degree of interaction and integration with on-chain resources (such as DeFi, NFT).

Web3 data security and anonymity: Focus on the protection of user privacy when tools process on-chain data, as well as data security in the Web3 environment.

Economic Model and Token Economics: Evaluate whether the tool’s business model incorporates token economics and how it leverages cryptocurrencies and token incentives to drive the ecosystem.

Nansen: A paragon of on-chain intelligence and in-depth analysis

Decentralization capabilities: Nansen excels in data integration and analysis, but its reliance on centralized data warehouses weakens its decentralization potential in a Web3 environment. In the future, Nansen needs to explore more decentralized storage and analysis solutions to strengthen its leading position in decentralized data processing.

Real-time data tracking and transparency: Nansen excels in real-time on-chain data monitoring, especially in monitoring token liquidity and large transactions. However, in terms of data transparency, users’ understanding of data sources and analysis logic still needs to be further strengthened.

Smart contract analysis capabilities: The smart contract analysis capabilities provided by Nansen are relatively comprehensive, especially in analyzing DeFi projects and NFT markets. In the future, Nansen needs to continue to strengthen its in-depth integration with smart contracts to provide richer interactive analysis.

Web3 data security and anonymity: Nansen has demonstrated high standards in terms of data security and privacy protection. However, with the development of the Web3 environment, Nansen needs to further strengthen its data processing and storage mechanism to better protect user privacy.

Economic Model and Token Economics: Nansen’s business model is primarily based on subscription services and has not yet extensively integrated token economics. Facing the future, Nansen may consider introducing a tokenized incentive mechanism to enhance user participation and ecosystem activity.

Dune Analytics: The forefront of community-driven and custom analytics

Decentralization capabilities: Dune Analytics excels in providing decentralized data analysis, especially its community-driven data sharing and analysis model. However, there is still room for improvement in the degree of decentralization of data storage and processing.

Real-time data tracking and transparency: Dune Analytics provides highly transparent data analysis and visualization, especially in community-created dashboards. This transparency and real-time nature brings deep market insights to users.

Smart contract analysis capabilities: Dune Analytics provides a high degree of flexibility and customization for smart contract analysis, but its depth and accuracy still need to be improved in some complex scenarios.

Web3 data security and anonymity: With the increasing importance of Web3 data security and privacy protection, Dune Analytics needs to continue to strengthen its measures in this area to protect user data and privacy.

Economic model and token economics: Dune Analytics’ business model is outstanding in terms of flexibility, but it is still in its infancy in terms of the integration of token economics. In the future, Dune can explore how to integrate token economics into its business model.

LookOnChain: The leader in real-time monitoring and market insights

Decentralization capabilities: As a data analysis platform based on social media, LookOnChain still has room for improvement in data decentralization, especially in the decentralization of data storage and processing.

Real-time data tracking and transparency: LookOnChain demonstrates its unique advantages in real-time tracking of whale accounts and large transactions, providing instant and transparent insights into the market.

Smart contract analysis capabilities: LookOnChain is relatively limited in in-depth analysis of smart contracts, and needs to strengthen its ability to analyze complex smart contract interactions in the future.

Web3 data security and anonymity: In the Web3 environment, LookOnChain needs to further strengthen data security and user privacy protection, especially in handling sensitive transaction data.

Economic model and token economics: LookOnChain’s business model is relatively simple and mainly relies on paying users and platform cooperation. In the future, we can explore integrating token economics into its development strategy to enhance user participation and ecological activity.

How to improve the presence of on-chain data analysis in a diversified way

Based on the above analysis, Nansen, Dune Analytics and LookOnChain have each demonstrated unique advantages and potential in the field of Web3 on-chain data analysis. They all have varying degrees of performance in decentralization capabilities, real-time data tracking, smart contract analysis, Web3 data security, and business models. We expect Nansen to solidify and even expand its leadership position in the market by expanding supported chains and enhancing analytical capabilities. Dune Analytics may continue to maintain its leading position in the field of Web3 data analysis by enhancing the community and improving tool capabilities. LookOnChain will improve its competitiveness in the market by cooperating with more platforms and data providers and enhancing its data analysis services.

Nansen: Integrating decentralized data storage and analysis

Develop a decentralized data warehouse: Nansen should explore the use of blockchain technology to store and process data to improve the decentralization of data. For example, we cooperate with hardware projects or even the currently popular DePin projects to enhance the security and non-tamperability of data on the one hand, and to further expand the high-end user market such as institutions on the other.

Real-time analysis of on-chain data: In order to provide more real-time market analysis, Nansen can develop smart contracts to monitor and analyze on-chain events in real time, such as large transactions and token liquidity changes. This will allow Nansen to provide instant market updates and trading opportunities.

Deepen Smart Contract and DeFi Analysis: Nansen should further deepen its smart contract analysis capabilities, especially in the DeFi ecosystem. For example, providing more in-depth risk assessment and return analysis for DeFi projects to help investors make more informed decisions.

Dune Analytics: Expanding the community-driven model

Community incentive mechanism: Dune Analytics can introduce a token incentive mechanism to encourage community members to create and share high-quality data analysis dashboards. This not only increases user engagement, but also enriches the platform’s data resources.

Improve decentralized data processing: Dune Analytics should explore decentralized data processing solutions, such as using decentralized computing resources to run complex data analysis. This will increase transparency and security of data processing. Dune has a very rich data source, which is their biggest capital for future integration with AI business.

Enhanced smart contract integration: Dune Analytics can further enhance integration with smart contracts, allowing users to interact with smart contracts directly from the dashboard, such as executing transactions and participating in DeFi protocols. Dune can even further explore becoming one of the preferred blockchain development platforms for Web3 developers. This will ensure that hot projects and potential narratives are born directly on Dune, rather than just interesting charts.

LookOnChain: Improving the depth of data analysis

Enhanced smart contract analysis capabilities: LookOnChain should enhance its smart contract analysis capabilities, especially for complex DeFi protocols and NFT projects. This can help users gain a deeper understanding of the inner workings and risks of these projects.

Expanding data sources and collaborations: LookOnChain can expand its data sources by partnering with more blockchain projects and data providers. This not only provides a more comprehensive view of the market, but also increases user trust in the accuracy of the data.

Reshaping the future of Web3 data analysis tools

1. Go beyond traditional models and toward true decentralization:

Traditional data analysis relies on centralized data storage and processing, but in the Web3 field, this model needs to be reshaped. Tools such as Nansen, Dune Analytics, and LookOnChain should explore data storage and analysis methods based on blockchain technology, such as ensuring data transparency and non-tamperability through distributed ledgers, or utilizing decentralized computing resources for data processing. This is not only a technological innovation, but also a fundamental change in data processing philosophy.

1. Real-time data analysis: from reaction to anticipation:

The future of Web3 data analysis tools lies in real-time and predictability. Tools should shift from simple data monitoring to intelligent systems capable of predicting market trends and identifying patterns. For example, through the use of machine learning and artificial intelligence technology, real-time analysis and prediction of market dynamics can be achieved.

1. Deep integration and interaction of smart contracts:

Web3 data analysis tools should integrate smart contract technology more deeply. This means not just analyzing smart contract data, but enabling tools to interact directly with smart contracts, providing richer functionality such as automated trading, risk assessment, and strategy execution.

1. Data Security and Privacy: A New Framework for Building Trust:

In the Web3 era, data security and privacy protection will become core competitiveness. By employing advanced technologies such as zero-knowledge proofs, data analysis tools can perform in-depth analysis without leaking sensitive user information, thereby building a more secure and trustworthy ecosystem.

1. Innovation in Token Economics:

Web3 data analytics tools should explore incorporating token economics into their business models and functionality. This is not limited to incentive mechanisms, but also includes using tokens as a medium of exchange, proof of stake, and governance tool to create a self-appreciating and sustainable ecosystem.

1. Future-proof agility:

Finally, Web3 data analysis tools must be agile and adaptable to respond to rapidly changing technology and market environments. This means continuous iteration, rapid integration of emerging technologies, and continuous optimization of user experience. Whoever iterates functions faster and optimizes products faster will be more likely to win.

The future development direction of Web3 data analysis tools is not only technological progress but also fundamental innovation like data analysis and business models. Providers of data are expected to become predictors of market dynamics, assistants for user decision-making, and active participants in the blockchain ecosystem, thus having a higher sense of presence.

The future development of these tools will be affected by many factors such as their technological innovation, market adaptability, user experience, business model and future development potential. As blockchain technology continues to advance and market demands change, these tools need to be continuously adjusted and optimized to maintain their competitiveness in the market.

Disclaimer：

1. This article is reprinted from [Mirror]. Forward the Original Title ‘链上数据产品洞察：Web3时代的数据分析革命’. All copyrights belong to the original author [Kyle Liu]. If there are objections to this reprint, please contact the Gate Learn team, and they will handle it promptly.
2. Liability Disclaimer: The views and opinions expressed in this article are solely those of the author and do not constitute any investment advice.
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