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In the rapidly evolving blockchain space today, on-chain data has become a core asset with an increasingly vital role in the ecosystem. From token transactions to NFT minting, every detail of on-chain activity paints a complete picture of value flow. In this data-driven era, on-chain data is much more than just piles of data. They offer a true reflection of market dynamics, user behavior, and the overall health of the blockchain ecosystem.
Marketing studies tell us that consumer behavior analyses discover profound future trends in the overall market. Similarly, in the world of Web3, in-depth analysis and insights into user behavior are of immeasurable value to market participants. Nansen, Lookonchain, and Dune Analytics, as leading data analysis projects in the crypto sphere, not only provide users with profound on-chain data analysis but also play an indispensable role in the development of blockchain technology. This study will delve into the characteristics of these three platforms and their significance for the development of blockchain technology.
On-chain data reflects user behavior. In the world of blockchain, on-chain data can represent identities such as individuals, institutions, exchanges, market makers, and more participating in on-chain activities. On-chain data analysis can provide insights into market trends and user behavior, discover potential opportunities and risks, enhance operational efficiency, reduce costs, support decision-making and strategic planning, and strengthen security and risk control. Through in-depth analysis of on-chain data, retail or institutional investors can gain the following benefits at a minimum:
Data support for decision-making: On-chain data provides investors and project teams with an objective perspective, helping them better understand the actual market situation and make wise investment decisions.
Optimization of market strategies: In-depth analysis of on-chain data helps project teams and traders understand market demand and changes, allowing them to adjust their market strategies accordingly.
Improved operational efficiency: By identifying bottlenecks and issues in operations, resource allocation and processes can be optimized.
Promoting innovation and R&D: Providing valuable feedback to project teams, helping them understand user needs, and staying in sync with market and user demands.
Enhancing transparency and trust: On-chain data provides an open and transparent platform for all participants in decentralized ecosystems, increasing trust in the system.
Discovering potential opportunities and risks: Helps identify market opportunities and potential risks, reducing exposure to risk.
Strengthening security and risk control: Real-time monitoring and analysis of on-chain data help detect abnormal behavior and risk events promptly, allowing for prevention and response.
Nansen, Dune Analytics, and LookOnChain, leaders in this field, each have unique features that allow them to provide users with unique and in-depth insights. We’ve analyzed these tools to reveal their respective strengths and limitations and explore future trends in data markets and their influence on investors.
Nansen provides a deep understanding of the crypto market through behavioral analysis of over 120 million wallet addresses. It primarily focuses on token holdings, exchange inflows and outflows, and smart contract activities. Through its labeling and alert systems, Nansen enables users to identify market trends and quickly capture investment opportunities.
In-Depth Token Analysis
Nansen’s analysis at the token level covers multiple dimensions, including changes in Smart Money holdings, fund flows in and out of exchanges, and tokens’ overall market performance. This comprehensive perspective allows investors to understand market dynamics from multiple angles and make more accurate investment decisions.
Starting from the market level, Nansen analyzes Smart Money’s trading activities daily and infers their trading intentions (large purchases: potential speculation opportunities; large sales: potential selling opportunities). This helps investors discover promising projects for investment. They can further research projects that they are not familiar with.
In the cryptocurrency and blockchain space, Smart Money’s actions are often considered indicators of market trends. Different Smart Money groups, such as “Flash Boys,” funds, and other large holders, have unique trading patterns and strategies. An in-depth understanding of these patterns and strategies can provide valuable trading signals and market insights to investors.
Flash Boys Trading Observations
Flash Boys typically pursue short-term profits, and their trading strategies often rely 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 are buying a token in large quantities, this may suggest short-term potential for price increases.
Risks: Because Flash Boys’ strategies are usually based on short-term trends, following their trades can involve higher risks. Investors need to ensure their trading strategies align with their risk tolerance.
Fund Trading Observations
Funds and other large holders tend to adopt more conservative and long-term investment strategies. Their trading decisions are often based on in-depth market research and fundamental analysis.
Trading Signals: Observing the trades of funds can provide clues about medium to long-term market trends. For example, if multiple large funds begin accumulating a particular token, it may suggest long-term growth potential for that token.
Strategies: Fund investment strategies are often more stable and systematic. By analyzing their trading patterns, investors can learn from their investment strategies to optimize their own portfolios. However, as crypto funds often have arrangements with their portfolio projects to receive released tokens regularly, their fund holdings and transfers may not always accurately reflect market trends. Investors need to exercise caution.
Smart Contract and Liquidity Provider Analysis
Nansen provides key metrics such as Annual Percentage Yield (APY) by tracking popular contracts and liquidity provider (LP) trading pairs. This data is crucial for evaluating the potential value and risks of DeFi projects.
Labeling System and Alert Mechanism Nansen’s labeling system and alert mechanism provide timely feedback on market dynamics. By tracking specific labels and wallet addresses, users can promptly receive critical market information and adjust their investment strategies quickly.
Nansen AI’s alert system is a powerful tool for cryptocurrency investors and project teams. It helps them stay updated on market dynamics, manage risks, and optimize strategies in a timely manner.
Comprehensive Coverage: Supporting multiple public chain networks allows investors to track dynamics across multiple markets, providing a more comprehensive market perspective.
Flexibility: Whether it’s tokens or NFT collections, users can choose and track according to their needs, offering great flexibility.
Tracking Smart Money: Users can add Smart Money wallet addresses to stay informed about their trading activity, thus helping them capture market opportunities or avoid risks.
Label Metric Filtering: The various label metrics provided by @nansen_ai allow users to set alert conditions more precisely, ensuring the relevance and accuracy of alerts.
Amount Filtering: Setting alerts based on transaction amounts helps users promptly capture large transactions and significant market movements.
Multi-Platform Integration: Alerts can be received on platforms such as Telegram and Discord. This ensures that users can receive timely alert notifications on multiple platforms.
In summary, Nansen’s AI system currently provides services similar to bots, based on pre-input addresses or pre-set metrics for tracking, and the user experience is similar to bot-based Telegram notifications. Currently, AI involvement in intelligent analysis is relatively low, mainly based on on-chain activity-related notifications, and it lacks some innovation and competitiveness from the current perspective. In the future, Nansen may focus on improving related products.
Dune Analytics offers powerful SQL-based data analysis capabilities that cover various aspects of the cryptocurrency and DeFi fields. Its community-driven model and open data access strategy make it a highly dynamic analytics platform.
Community Sharing and Collaboration Dune’s community culture encourages data sharing and collaboration, providing users with an ever-evolving data analysis environment. Users can easily access and modify others’ analytical dashboards, creating new perspectives that adapt to market changes.
Powerful 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 exceptionally adaptive tool, especially for advanced users with specific data requirements. Furthermore, Dune Analytics’ comprehensiveness is another key reason for its popularity. It supports data analysis on multiple public chains, offering users a comprehensive market perspective. Regardless of which project or area users are interested in, they can find detailed data and in-depth analysis on Dune.
Ease of Use Dune Analytics’ powerful features and user-friendly design make it easy to use.
Dune allows users to zoom in, go full screen, and select any portion of charts, providing a highly customizable experience for viewing and analyzing data according to their needs.
Through the Fork feature, users can easily duplicate the entire dataset into their workspace. This design encourages exploration and experimentation while providing a secure environment for modifications and innovations that do not affect the original dataset.
3. Queries and Code Transparency
The Query feature allows users to view the code of any dataset, increasing transparency and enabling experienced users to understand the data’s sources and processing methods in depth.
4. Search and Sorting Functions
Dune’s search feature enables users to quickly search related dashboards and sort them by popularity, bookmarks, and release dates. This significantly improves users’ work efficiency, making it easier for them to find and analyze relevant data.
Dune encourages users to copy successful datasets through Fork and allows them to modify the code. This design lowers the entry barrier for users, who can start with existing datasets and then adjust according to their needs.
Compared to Nansen, Dune’s advantage lies in its customizable design for relevant data. Users can create their own data dashboards based on open APIs, providing more freedom, higher flexibility, and greater composability. Currently, many projects choose to disclose their related transactions and operational data on Dune, serving as a data reference for users and investors. Nansen, on the other hand, has formed more “structured” data services that are more suitable for institutional users and beginners. In the future, Dune may introduce a reward mechanism to incentivize developers who create dashboards, promoting the development of the entire Dune ecosystem.
LookOnChain is best known through its Twitter account and for its in-depth tracking of whale wallets. It provides users with a unique perspective on market dynamics, especially on the behavior of large investors.
Whale-Oriented Strategy
By focusing on significant whale wallets, LookOnChain allows users to grasp major market trends quickly. This strategy is particularly suitable for investors who wish to follow market leaders. Through LookOnChain, investors can not only access the trading records of these wallets but also gain insights into their strategies and motivations. Such information is highly valuable for investors seeking success in the cryptocurrency market. After all, having the right information and strategy is the key to success in a market full of variables. Therefore, LookOnChain offers investors a unique opportunity to understand the market better and make wise investment decisions.
Deeper Analysis through Debank Connection LookOnChain also connects to DeBank’s database for a deeper analysis of whale wallets. Such in-depth analyses help users better understand the strategies and market trends of these large wallets.
Each of these three platforms represents different aspects of on-chain data analysis. Nansen provides users with a comprehensive perspective through its in-depth wallet behavior analysis and real-time data updates. Dune Analytics, on the other hand, offers a collaborative and innovative environment for data analysts and programmers with its powerful customization features and community-sharing culture. LookOnChain, with its simple and intuitive approach, enables even ordinary users to grasp market dynamics quickly.
Data analytics is an indispensable infrastructure in the crypto industry. Data analysis platforms not only assist investors in making investment decisions but also aid in AML and crime tracking. On-chain behavior analysis is one of the selling points of data-oriented platforms, with the advantage of early discovery of potential investment opportunities and the drawback of risks associated with the uncertainty of investment opportunities. Regardless, the information provided by on-chain data should be used as supplementary information for decision-making. Investors need to make precise decisions based on their own judgment and the actual situation.
Nansen: Institutional Think-Tank
To accommodate various types of users, Nansen offers three service levels: $150 per month (Standard), $1500 per month (VIP), and $2500 per month (Alpha). Subscribers can access research reports and project analyses produced by the Nansen team and interact with its professional research analysts.
Nansen hasn’t introduced a token yet.
Dune Analytics: Developer Community-Oriented
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 queues for query execution, export results, create more than 1 private dashboard, or remove watermarks, they may need to upgrade to “Plus” or “Premium” plans, which currently cost $349 per month and $849 per month respectively. Besides offering more rich features, they also provide more API calls per minute. These premier offerings help to deepen the connections between the platform and its professional or enterprise users. They could potentially transform the platform from an external data provider to a core infrastructure provider.
Dune Analytics hasn’t introduced a token yet.
LookOnChain: Useful Tool for Trend-Following
LookOnChain currently provides free data analytics to users on X (formerly Twitter). For the time being, its revenue sources include paid users who can access their Pro Channel on Telegram and a split of transaction fees on user referrals to crypto exchanges. LookOnChain hasn’t introduced a token yet, either.
When comparing these three blockchain data analysis tools, we find that Nansen, Dune Analytics, and LookOnChain each exhibit 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 a unique advantage in providing intuitive market insights.
Technical Innovation
Nansen’s technical innovation is evident in its ability to conduct in-depth analysis of over 120 million wallet addresses. Its core strength lies in its comprehensive analysis of token holdings and smart contract activities, which provides users with a holistic view of the market. However, behind this technological prowess is an overreliance on tagged addresses, which may result in blind spots regarding emerging or untagged addresses.
Dune Analytics demonstrates its outstanding SQL capabilities in data processing. This capability not only places it at the forefront of data analysis but also provides the developer community with powerful custom tools, which is rare in the market. We have high expectations for this model.
LookOnChain innovates by directly tracking the transaction dynamics of large investors (whale wallets). This is crucial for quickly capturing market trends, especially in the highly volatile cryptocurrency market.
Market Adaptability
Nansen showcases extensive adaptability to the blockchain ecosystem by supporting multi-chain data analysis. However, this breadth may lead to a dispersion of focus, affecting in-depth analysis of specific chains or market segments. We did encounter this limitation in our usage of Nansen, as it may not promptly follow hot sectors or analyze data of narrative-based currencies.
Dune Analytics rapidly adapts to market changes through its open community culture and user-friendly interface design. This flexibility makes it the preferred choice for users seeking quick responses and deep insights.
LookOnChain swiftly adapts to market dynamics driven by social media, leveraging the popularity of the Twitter platform. However, it also carries the risk of overreliance on a single platform.
User Experience
Nansen offers a highly personalized experience with its tagging system and alert system. However, for beginners, the complex user interface implies a steep learning curve.
Dune Analytics earns high marks for user experience with its straightforward SQL interface and rich community content. Its user-friendliness attracts both technical and non-technical users, creating a win-win situation.
LookOnChain provides an excellent experience for non-technical users with its intuitive information display and simple user interactions. However, the depth and breadth of its information may sometimes not meet the demands of more advanced users.
Business Model and Profitability
Nansen’s multi-tiered subscription service reflects its deep understanding of various user groups. This differentiation strategy enhances its market coverage and ensures a stable income stream.
Dune Analytics showcases a flexible business model by offering free services and premium subscription options. This strategy maintains an active community and presents profit potential.
LookOnChain complements its business model by leveraging its huge Twitter following. However, the sustainability and stability of this model require further validation.
In response to the features of Web3 blockchain data analysis tools, we have further optimized the traditional multidimensional business evaluation model to make it more targeted. This optimized model, which we name the Onchain Data Tools Analysis Evaluation(ODTEF), places greater emphasis on the characteristics of blockchain technology and the uniqueness of data tools in the Web3 environment. The main evaluation dimensions include the following aspects:
It is the degree of decentralization in data management and analysis processes, including the level of decentralization in data storage, processing, and accessibility.
This evaluates whether the analysis tools can provide real-time monitoring of on-chain data and their data transparency and traceability.
This examines the tool’s capability to analyze smart contracts and its level of integration and interaction with on-chain resources such as DeFi and NFTs.
This focuses on the tool’s protection of user privacy when handling on-chain data and its data security in the Web3 environment.
This involves assessing whether the tool’s business model incorporates token economics and how it utilizes cryptocurrency and token incentives to drive the ecosystem.
Nansen excels in data integration and analysis, but its reliance on centralized data warehouses reduces its potential for decentralization in the Web3 environment. To strengthen its position in decentralized data processing, Nansen should explore more decentralized storage and analysis solutions in the future.
Nansen demonstrates excellent real-time monitoring of on-chain data, especially in tracking token liquidity and large transactions. However, there is room for improvement in terms of data transparency, particularly in increasing user understanding of data sources and analysis logic.
Nansen offers relatively comprehensive smart contract analysis services, particularly in analyzing DeFi projects and the NFT market. In the future, Nansen should continue to deepen its integration with smart contracts to provide richer interactive analysis functions.
Nansen upholds high standards for data security and privacy protection. However, as the Web3 environment evolves, Nansen needs to strengthen its data processing and storage mechanisms further to protect user privacy better.
Nansen’s business model primarily relies on subscriptions and has not yet integrated token economics. Looking ahead, Nansen could consider introducing token-based incentive mechanisms to enhance user engagement and ecosystem vitality.
Dune Analytics shines in providing decentralized data analysis, especially through its community-driven data sharing and analysis model. However, there is room for improvement in the degree of decentralization in data storage and processing.
Dune Analytics offers highly transparent data analysis and visualization, especially in community-created dashboards. This transparency and real-time data access provide users with deep market insights.
Dune Analytics provides a high degree of flexibility and customization in smart contract analysis. However, depth and precision can be improved, especially in complex scenarios.
With the increasing importance of Web3 data security and privacy protection, Dune Analytics should continue to enhance its efforts in this regard to safeguard user data and privacy.
Dune Analytics’ business model excels in flexibility but is in the early stages of considering token integration. In the future, Dune can explore ways to incorporate token economics into its business model.
LookOnChain, as a social media-based data analysis platform, has room for improvement in data decentralization, particularly in decentralized data storage and processing.
LookOnChain demonstrates unique strengths in real-time tracking of whale accounts and large transactions, providing the market with instant and transparent insights.
LookOnChain has relatively limited capabilities in deep smart contract analysis, particularly for complex interactions. It should enhance its analysis capabilities in this regard.
In the Web3 environment, LookOnChain should further strengthen data security and user privacy protection, especially when handling sensitive transaction data.
LookOnChain’s business model is relatively simple, relying mainly on paid users and partnerships. In the future, it can explore integrating token economics into its development strategy to enhance user participation and ecosystem vitality.
Based on the above analysis, Nansen, Dune Analytics, and LookOnChain each exhibit unique strengths and potentials in the Web3 blockchain data analysis field. They have varying characteristics in decentralization, real-time data tracking, smart contract analysis, Web3 data security, and business models. We anticipate that Nansen will consolidate or expand its leadership position in the market by extending support for additional chains and enhancing analytical capabilities. Dune Analytics may continue to maintain its leadership position by strengthening its community and enhancing tool functionality. LookOnChain could enhance its competitiveness by collaborating with more platforms and data providers and improving its data analysis services.
Nansen should explore using blockchain technology for data storage and processing to enhance decentralization. Collaborating with hardware projects, including DePIN projects, could enhance data security and immutability while expanding its reach to high-end users, including institutions.
To provide more real-time market analysis, Nansen can develop smart contracts to monitor and analyze on-chain events, such as large transactions and token liquidity changes. This will enable Nansen to offer real-time market dynamics and trading opportunities.
Nansen should further deepen its smart contract analysis capabilities, especially within the DeFi ecosystem. For example, providing more in-depth risk assessments and yield analyses for DeFi projects can help investors make more informed decisions.
Dune Analytics can introduce token-based incentive mechanisms to encourage community members to create and share high-quality data analysis dashboards. This can increase user engagement and enrich the platform’s data resources.
Dune Analytics should explore decentralized data processing solutions, such as using decentralized computing resources to run complex data analyses. This will improve data processing transparency and security. Dune has a wealth of data sources, which can be a significant asset when it chooses to introduce AI-driven solutions.
Dune Analytics can further enhance its integration with smart contracts, allowing users to interact directly with smart contracts from dashboards, such as executing transactions and participating in DeFi protocols. Dune can even explore becoming a blockchain development platform for Web3 developers. If so, it may become the birthplace of the next killer projects or hyped narratives rather than merely insightful charts.
LookOnChain should enhance its ability to analyze smart contracts, especially those of complex DeFi protocols and NFT projects. This can help users gain a deeper understanding of the inner workings and risks of these projects.
LookOnChain can expand its data sources by collaborating with more blockchain projects and data providers. This will not only provide a more comprehensive market perspective but also increase user trust in data accuracy.
Traditional data analysis relies on centralized data storage and processing, but in the Web3 domain, this model needs a fundamental reshaping. Tools like Nansen, Dune Analytics, and LookOnChain should explore data storage and analysis methods based on blockchain technology, such as ensuring data transparency and immutability through distributed ledgers or utilizing decentralized computing resources for data processing. This will not only be a technological upgrade but also a fundamental change in data processing philosophy.
2. Real-Time Data Analysis: From Reacting to Anticipating
The future of Web3 data analysis tools lies in real-time and anticipatory capabilities. Tools should evolve from simple data monitoring to intelligent systems capable of predicting market trends and identifying patterns. For instance, by employing machine learning and artificial intelligence techniques, real-time analysis and forecasting of market dynamics can be achieved.
3. Deep Integration and Interaction with Smart Contracts
Web3 data analysis tools should integrate smart contract technology more deeply. This means not only analyzing data from smart contracts but also enabling tools to directly interact with them, providing richer functionalities such as automated trading, risk assessment, and strategy execution.
4. Data Security and Privacy: Building a New Trust Framework
In the Web3 era, data security and privacy protection will be a core competitive advantage. By adopting advanced technologies like zero-knowledge proofs, data analysis tools can conduct in-depth analysis without exposing users’ sensitive information, thereby constructing a more secure and trustworthy ecosystem.
5. Innovation in Token Economics
Web3 data analysis tools should explore integrating token economics into their business models and functionalities. This goes beyond incentive mechanisms and includes using tokens as exchange mediums, proof of stake, and governance tools, thus creating a self-sustaining and evolving ecosystem.
6. Future-Oriented Agility
Lastly, Web3 data analysis tools must possess agility and adaptability to respond to rapidly changing technological and market environments. This entails continuous iteration, swift integration of emerging technologies, and ongoing optimization of user experiences. Those who iterate faster and optimize products more efficiently are more likely to succeed.
The future of Web3 data analysis tools lies in technological advancements and a fundamental reinvention of data analysis and business models. Data providers have the potential to become more present as predictors of market dynamics, assistants in user decision-making, and active participants in the blockchain ecosystem.
Factors such as technological innovation, market adaptability, user experience, business models, and growth potential will influence the future development of these tools. As blockchain technology advances and market demands evolve, these tools must continuously adjust and optimize to remain competitive.
Also published here.