Insight Data Issue 06 | OKX Web3 & Nansen: The Nine Essential Data Hurdles Every Web3 Beginner Must Overcome
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Insight Data Issue 06 | OKX Web3 & Nansen: The Nine Essential Data Hurdles Every Web3 Beginner Must Overcome
Focusing on fundamental issues commonly faced by beginners.
Navigating Web3 tides with focused insightsSummary: In the cryptocurrency market, data has always been a crucial basis for making trading decisions. How can we cut through the fog of data to uncover effective insights that optimize our trading strategies? This remains an ongoing topic of interest. As part of its special series "Insights into Data," OKX has partnered with leading industry data platforms such as NanSen, CoinGlass, AICoin, Coingecko, and 0xScope to develop a more systematic methodology around common user needs, offering valuable reference and learning resources for the broader market.
Below is the sixth installment, jointly produced by the OKX Web3 team and NanSen team, focusing on topics like “9 Fundamental Questions Every Web3 Beginner Must Address.” We hope you find it helpful.
About Nansen: Nansen is a blockchain analytics platform that enriches on-chain data using millions of wallet labels. It helps crypto users discover opportunities, conduct due diligence, and protect their portfolios via real-time dashboards and custom alerts.
About OKX Web3: The team brings together top-tier talent with deep technical expertise and extensive industry experience. For years, they have continuously innovated and practiced within the Crypto space, consistently prioritizing user experience and security. Currently, the OKX Web3 Wallet stands as one of the most comprehensive decentralized multi-chain wallets available, supporting over 90 blockchains and integrating five core modules: wallet, trading, NFT marketplace, DeFi, and DApp discovery. Users can access multi-chain tokens, NFTs, and DeFi assets across mobile app, browser extension, and web platforms.
1. What fundamental data dimensions should beginners focus on when entering the Web3 world?
Nansen: The easiest way to learn on-chain data is through hands-on practice—such as swapping tokens on a decentralized exchange (DEX)—and then looking up the transaction on a block explorer like Etherscan. Being able to read detailed transaction information on a block explorer is at the heart of understanding Web3 data analysis.
Beginners should first focus on transaction data, then gradually progress to traces and logs. A potential learning path could be: start by learning how to interpret easy-to-understand aggregated transaction data (e.g., via Nansen or DeBank), then explore raw transaction data (using a block explorer), dive into traces and logs (again via a block explorer), and finally analyze raw data provided by analytics platforms (like Nansen). Browsing block explorers forms the foundation for understanding these data layers.
There is a vast amount of activity-based data on blockchains, but how do we truly understand what’s happening? Fortunately, EVM-compatible chains are standardized, and most interaction data is stored in several common tables:
• Transactions: Detailed records of each transaction, including sender, receiver, amount, gas fee, and timestamp.
• Traces: Step-by-step operation records during a transaction, covering function calls, transfers, and smart contract executions.
• Logs: Event logs generated by smart contracts to record specific events, often used to track state changes and notifications.
These tables allow users to deeply examine on-chain activities—such as analyzing transaction patterns, tracking fund flows, and understanding smart contract behavior. This data not only reveals details about individual transactions but also uncovers broader market trends and behavioral patterns.
OKX Web3: We recommend new users interested in Web3 pay attention to three key data dimensions: market data, network data, and community & development data.
Firstly, market data includes:
• Price data: Real-time and historical price information for cryptocurrencies and tokens.
• Market cap: Total value of a cryptocurrency or token, calculated as current price multiplied by circulating supply.
• Trading volume: Number of units traded within a given time period.
• Transaction history: Records of blockchain transactions, including sender, receiver, amount, and timestamp.
Secondly, network data refers to node distribution and gas fee dynamics. Geographic and logical distribution of nodes affects decentralization and security, while gas prices, gas limits, and priority fees reflect network usage levels.
Lastly, community and development data includes developer activity and community engagement. Key metrics include number of active developers, code commits, contributions to blockchain projects, as well as data on community size and activity levels. These can be gathered from forums, social media, and events—most Web3 discussions today happen on Twitter, Telegram, and Discord.
2. How can analyzing blockchain transaction data help identify market trends?
Nansen: For beginners, analyzing on-chain transaction behavior is key to understanding market trends, providing deep insights into actual blockchain conditions. Unlike traditional finance (TradFi), all blockchain transactions are public and transparent, enabling us to interpret and analyze them—and gain deeper market visibility than in TradFi, such as identifying who is buying or selling. Using on-chain data, we can perform various analyses—for example, determining daily active user counts and their behaviors. We can query all daily addresses to see their counterparties, or use data providers to automate this process.
Specifically, we can explore active address distributions, top entity behaviors, number of smart contract deployments, trading volumes, and cross-entity user preferences. These insights go beyond surface-level observations. With tools like Nansen's smart money and wallet labeling features, we can dig deeper into market trends—such as identifying which wallets are accumulating certain assets, which entities wield influence, and how their actions may impact the market.
Through such analysis, novice users not only grasp basic on-chain transaction mechanics but also uncover complex underlying market dynamics, allowing for more informed trading decisions. This transparency and accessibility represent a major advantage of blockchain over traditional finance, empowering every participant to better understand the market.
OKX Web3: We believe new users analyzing on-chain trading data should monitor movements of major assets like stablecoins, BTC, and ETH, while also paying attention to overall on-chain market热度.
First, stablecoin trading and circulation volumes reflect market sentiment. During uncertain or volatile periods, users often move funds into stablecoins to hedge risk. Additionally, inflows and outflows of stablecoins indicate liquidity shifts—large inflows into exchanges may signal upcoming buying pressure, while significant outflows may suggest selling pressure.
Monitoring BTC and ETH dominance is also important, reflecting their share of total market capitalization. Rising BTC dominance suggests stronger market preference for Bitcoin, whereas rising ETH dominance indicates greater interest in Ethereum and associated DeFi projects. Analyzing these dominance metrics helps reveal market participants’ buying preferences.
Meanwhile, on-chain market热度 serves as another vital indicator.
Increased trading volume typically signals higher market activity, potentially leading to greater price volatility. Sustained high volume confirms trend strength—for instance, in bull markets, rising prices accompanied by high volume indicate strong upward momentum. Moreover, growing numbers of active users suggest increasing participation on a particular cryptocurrency or blockchain platform, possibly driving price increases. Ultimately, active user count is a critical health metric for blockchain projects—high engagement usually correlates with strong community support and sustainable growth prospects. By monitoring these indicators, beginners can better understand market dynamics and make smarter trading decisions.
3. What information does smart contract interaction data contain? Which metrics should beginners prioritize?
Nansen: Smart contract interactions in crypto contain key details such as involved addresses, functions called, tokens transferred, gas paid, and input data. For beginners, the first step is understanding who initiated the transaction and what function was invoked. Once you can read block explorers, you’ll gain a much clearer picture of how smart contracts interact with wallets and other contracts.
OKX Web3: Smart contract interactions include many critical pieces of information essential for understanding their behavior and implications. Here are six key elements:
1. Transaction Simulation:
The purpose of simulating a transaction is to predict the outcome of interacting with a smart contract before executing it on-chain. The key is to understand expected state changes, potential errors, and gas costs. Beginners should use transaction simulators to better anticipate how their actions affect the blockchain and avoid costly mistakes.
2. Permit2, Approval Amount:
Granting a smart contract permission to spend a specific amount of tokens on behalf of a user is highly significant. Key details include the maximum allowable spending amount and approval duration. Beginners should monitor approval amounts carefully to prevent over-authorization and potential token theft.
3. Gas Fees:
Gas fees refer to the cost of executing a transaction on the blockchain. Key metrics include gas price (cost per unit of gas), gas limit (maximum gas allowed), and total gas cost. Understanding gas fees helps beginners manage transaction costs and prioritize execution during network congestion.
4. Receiver Address (To-Address):
This is the destination address of a transaction. The key detail is ensuring the correct target address for the transaction or interaction. Beginners must verify the receiver address to ensure funds and interactions reach the intended destination and avoid asset loss.
5. Ownership:
Ownership determines who controls a smart contract or its assets. The key detail is identifying the address or entity with administrative control. Beginners should check ownership to understand governance structure and assess centralization-related risks.
6. Upgradability:
Upgradability indicates whether a smart contract can be modified after deployment. Key details include the existence of upgrade mechanisms and the conditions under which upgrades occur. Understanding upgradability is crucial for evaluating stability and security, as upgradable contracts can be altered by owners, introducing new risks.
4. How can wallet tracking tools help new users understand market movements?
Nansen: Wallet tracking tools provide deep insights by displaying key metrics in a single view.
These include wallet net worth, protocols used, and decoded transaction features that simplify interpretation. Nansen offers entity-level breakdowns, allowing users to see all addresses, net worth, used protocols, and decoded cross-chain transactions of a specific entity in one place. For newcomers unfamiliar with market dynamics, these tools help track complex wallets and inform trading decisions.
OKX Web3: Wallet tracking tools can offer valuable market insights for new users.
First, these tools visualize fund flows between wallets, exchanges, and protocols, helping users understand liquidity trends and identify potential buy/sell pressure. Tracking whale (large holder) movements also provides important signals, as their trades can significantly influence market trends.
Second, these tools allow users to view asset allocations across different wallets, helping them understand successful traders’ strategies. By analyzing wallet holdings, users can identify popular protocols or projects and make more informed investment choices.
Finally, monitoring buying and selling activity across wallets reveals overall market sentiment—whether players are bullish or bearish. Sudden large inflows or outflows into an asset can signal shifts in sentiment, helping users anticipate potential market moves.
Users can try some analytical tools—for fundamental analysis, consider these platforms:
1. Dune: Offers customizable queries and dashboards for tracking on-chain activity.
2. Artemis: Focuses on DeFi project analysis, delivering comprehensive insights into protocol performance and user activity.
3. DefiLlama: Specializes in DeFi analytics, providing TVL and other key metrics across protocols.
4. Rootdata: Delivers detailed data on various blockchain projects, including performance metrics and ecosystem analysis.
5. Glassnode: Focuses on on-chain data, offering a range of indicators to assess blockchain network health and activity.
6. Nansen: Combines on-chain data with wallet labels to provide insights into fund flows, wallet holdings, and market trends.
7. Blave: An emerging tool offering data analytics and insights into blockchain projects and market activity.
For sentiment analysis, refer to data from these three products:
1. Santiment: Provides on-chain, social, and development data to analyze market sentiment and detect trends.
2. Mest: Aggregates social media and community sentiment data to deliver market mood insights.
3. Kaito: Integrates multiple data sources, including social media, to offer a holistic view of market sentiment.
Learning to use these tools efficiently enables users to better understand market dynamics, spot trends early, and make smarter trading decisions.
5. When analyzing DeFi protocols, which key metrics should be prioritized?
Nansen: When researching different DeFi protocols, we evaluate multiple metrics, which may vary by application. While no single metric gives a complete picture, focusing on certain key indicators can be particularly helpful when seeking new opportunities.
In lending protocols, metrics like TVL (Total Value Locked), utilization rate, and user count serve as starting points for assessing overall platform activity. However, when evaluating new opportunities, tracking significant inflows into a project can be especially telling. Major fund inflows may indicate new liquidity provisioning activities in certain pools—potentially a good opportunity for yield-seeking traders.
Another key metric is examining the types of entities or depositors visible within the protocol—whether funds come from whales, smart contract wallets, or preferred DeFi wallets. These can act as potential counterparties. Note that these metrics don’t cover risk, which must be considered separately when using DeFi protocols.
OKX Web3: We recommend monitoring several dimensions: on-chain data, community feedback, team and builders, among others.
First, on-chain data includes TVL and trading volume. TVL measures protocol scale and popularity—high TVL reflects user trust and widespread adoption. Trading volume reflects protocol activity and liquidity—high volume generally indicates strong demand and confidence.
Second, community feedback includes engagement and sentiment on Twitter, Telegram, and Discord. Positive discussions on these platforms reflect community interest and project recognition—key indicators of participation and satisfaction. Team background and backing from reputable investors are also important factors in assessing a project’s potential.
Additionally, longevity matters—project history and sustained development activity. A long-running, actively developed project tends to be more reliable and durable.
Finally, smart contract audits by third parties reveal potential vulnerabilities and security risks, ensuring user fund safety. Together, these dimensions offer a comprehensive assessment of a project’s health and market potential.
6. How are address labels used in on-chain data analysis? What practical value do they offer?
Nansen: Although blockchain data is technically public, it’s often difficult to interpret because most of it isn’t human-readable. Address labels transform massive datasets into digestible formats. At a high level, address labels are how we tag and identify wallet addresses based on their on-chain behavior/actions. Given millions of addresses with diverse footprints, labels enable us to categorize wallets by behavior, allowing users to quickly find what they need.
The exact identity of wallet owners is usually unknown, but we classify and label wallets using tags and emojis. These can be simple, like “Dex Trader” (indicating DEX usage), or more sophisticated and useful, such as our “7d Smart Dex Trader” segment—the most profitable DEX traders over the past 7 days. By tagging the largest wallet database, our users gain insight into the types of wallets conducting trades and can discover high-signal addresses relevant to their interests or needs.
OKX Web3: Generally, address labels serve three main purposes:
First, identity identification and management: Labels help associate specific individuals, entities, or organizations with addresses. For example, labeling an address as “Exchange A” or “XYZ” aids in tracking transaction history and activity types (deposits, withdrawals, trades), facilitating classification and analysis.
Second, risk management and compliance: Labels help create whitelists (trusted) and blacklists (risky) addresses. This is crucial for monitoring and mitigating risks—preventing funds from flowing to fraudulent or illicit addresses, aligning with AML (anti-money laundering) and KYC frameworks.
Third, market analysis and research: Labeled addresses aid behavioral analysis—understanding user trading patterns, preferences, and fund flow paths. This is highly useful for market research and user behavior studies. Combined with other data like social signals and market indicators, it helps assess participant activity levels and trading strategies.
7. Why is on-chain fund flow analysis important?
Nansen: Fund flow analysis is crucial because it reveals buying and selling behaviors. As some of the most informed market participants, fund managers' actions often carry directional significance. Following their moves allows users to make timely, informed decisions.
Once you observe inflows or outflows over a specific period, further analysis is needed to understand motivations. For example, large inflows might signal preparation for fund distribution elsewhere—or merely internal rebalancing. For outflows, the key is tracing where funds ultimately go. For instance, both staking and deposits count as outflows, but imply very different intentions.
OKX Web3: On-chain fund flow analysis is a critical market research tool, revealing market sentiment and emerging trends to inform trading decisions.
First, analyzing fund flows helps determine overall market sentiment. Large inflows into an asset typically signal optimism, while heavy outflows may reflect pessimism. Second, changes in fund flows often precede market trend shifts—sustained inflows may foreshadow price increases, while persistent outflows may warn of declines.
In terms of risk management, fund flow analysis helps detect anomalies—such as sudden large transfers—that could indicate market manipulation or impending large trades. Monitoring whale movements is especially valuable, offering key insights that help users anticipate price swings and adjust strategies accordingly.
Finally, in decision-making, fund flow analysis offers a powerful perspective. Understanding how capital moves across assets or protocols helps optimize portfolio allocation, uncover new opportunities, and identify arbitrage possibilities.
Today, excellent on-chain analytics tools like Nansen and GlassNode offer detailed fund flow analysis, whale tracking, and transaction pattern recognition—providing beginner users with strong market insights and decision support. Notable tools include Nansen, which delivers comprehensive on-chain data including fund flows, whale movements, and trading patterns; and GlassNode, which provides broad on-chain metrics such as fund flows, trading volume, and active addresses.
8. What is holder analysis? How can token distribution help assess a project’s health?
Nansen: Holder analysis involves studying the distribution and behavior of wallet addresses holding a specific token, which can reveal patterns, concentration levels, and potential market impacts.
If a token is heavily concentrated in private wallets or known pump-and-dump actors, it's usually a red flag. You should also examine how much the development team or individuals hold, along with vesting schedules. Tools like Nansen allow users to observe token distribution at both address and entity levels. When analyzing addresses, it's important to distinguish between contract addresses and externally owned accounts (EOAs), and whether they belong to centralized exchanges (CEX), multisig wallets, or other entity types—this leads to a more comprehensive evaluation of project health.
OKX Web3: When evaluating the health of a token ecosystem, distribution insights are a vital metric:
First, analyzing holder distribution reveals whether tokens are concentrated among a few large holders or widely distributed among many small ones. A well-distributed structure generally supports market stability and reduces manipulation risks by large entities.
Second, trader behavior reflects market activity and sentiment: Observing holder trading activity offers deep insight into market mood. High-frequency trading may suggest speculation, while long-term holding reflects confidence in the project’s future.
Furthermore, project stability is closely tied to holder distribution: A stable and diversified holder base supports price resilience. This makes the project less vulnerable to mass sell-offs or speculative attacks, supporting long-term sustainable growth even amid market volatility.
Of course, community support and trust are foundational to project growth: A broad and active holder base reflects community size and engagement. Such grassroots support is crucial for adoption, development, and navigating market challenges.
9. What role do social signals and sentiment analysis play in Web3 data analysis?
Nansen: Social signals and market sentiment guide on-chain actions—and vice versa. On-chain data provides a way to verify social and emotional signals, letting people see who is actually buying or selling and what’s really happening.
OKX Web3: Sentiment indicators play a critical role in trading decisions. By analyzing social signals and sentiment data, we can effectively measure market participants’ emotional states toward specific projects or assets—whether optimistic, pessimistic, or neutral. These sentiment metrics directly influence trader psychology and market behavior, serving as key references for gauging market atmosphere and forecasting price movements.
Predicting market trends is one of the key applications of sentiment analysis. Combining social signals and sentiment data enables users to forecast short- and long-term market directions. For example, positive sentiment may precede price increases, while negative sentiment could lead to declines. Sentiment analysis provides real-time feedback, helping traders promptly adjust strategies and risk management plans.
Assessing project and market acceptance also relies on social signals and sentiment analysis. By monitoring online discussions, we can gauge how well-received a project or technology is within the community. Active and positive social media conversations often indicate broad recognition and support—critical for project teams adjusting strategy and roadmap.
Finally, sentiment analysis plays a vital role in risk management and market intelligence. Acting as an early warning system for market dynamics and event risks, it can quickly detect sudden negative sentiment or social media spikes—potential signs of instability or adverse events. Combined with on-chain data and market indicators, sentiment analysis helps comprehensively understand and monitor the health and evolution of the market.
Conclusion
The above is the sixth episode of OKX’s “Insights into Data” series, focusing on foundational questions commonly faced by beginners, aiming to offer practical guidance. In future articles, we will continue exploring more practical data usage and analysis methods, providing reference material for traders and newcomers seeking to learn trading and understand the industry.
Risk Warning and Disclaimer
This article is for informational purposes only. The content reflects the author's views and does not represent the position of OKX. This article is not intended to provide (i) investment advice or recommendations; (ii) offers or solicitations to buy, sell, or hold digital assets; or (iii) financial, accounting, legal, or tax advice. We do not guarantee the accuracy, completeness, or usefulness of the information provided. Holding digital assets (including stablecoins and NFTs) involves high risk and may experience significant price fluctuations. You should carefully consider whether trading or holding digital assets is suitable for you based on your financial situation. Please consult your legal/tax/investment professionals regarding your specific circumstances. You are solely responsible for understanding and complying with applicable local laws and regulations.
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