Insight Data Issue 05 | OKX Web3 & 0xScope: On-chain Data Analysis Guide, How Can Beginners Take the First Step?

Author: OKX

Abstract

In the cryptocurrency market, data has always been an important tool for making trading decisions. How can we cut through the data fog and uncover effective data to optimize trading decisions? This is a topic of ongoing interest in the market. This time, OKX has specially planned the "Insight Data" column and collaborated with industry data platforms such as CoinGlass, AICoin, Coingecko, and 0xScope to explore a more systematic data methodology based on common user needs for market reference and learning.

The following is the content of the fifth issue, developed by the OKX Web3 team in collaboration with the 0xScope team, focusing on topics such as "how to establish an on-chain data analysis methodology," hoping to be helpful to you.

About 0xScope: 0xScope is a leading data analysis and AI data provider in Web3. It is creating a universal Web3 LLM aimed at reducing the difficulty users face in understanding and interacting with Web3 through AI. This is thanks to the rich variety of Web3-related data accumulated by the 0xScope team since 2022, which has been adopted by nearly 200 Web3 professional institutions. Currently, Scopescan and Scopechat under 0xScope have collectively gained over 1 million users.

About OKX Web3: The team brings together top talents with a strong technical background and rich industry experience, continuously innovating and practicing in the Crypto field over the years, with a sustained focus on user experience and security. Currently, the OKX Web3 wallet is one of the most comprehensive decentralized multi-chain wallets on the market, supporting over 90 public chains, with five major sections: wallet, trading, NFT marketplace, DeFi, and Dapp discovery. Users can view multi-chain tokens, NFTs, and DeFi assets through the App, plugin, and web.

1. Why is on-chain data analysis important, and how should beginners take the first step?

0xScope: First, it is necessary to understand basic concepts and logic, such as address, amount, from, to, and gas fees. Try to use and understand the most basic blockchain explorers, and then use other tools for more detailed analysis.

Generally, commonly used analysis platforms or tools include on-chain data platforms, blockchain explorers, and API interfaces. On-chain data platforms (such as ScopeScan, ScopeChat, Nansen, Glassnode, and Dune Analytics) provide convenient data access and analysis functions. Blockchain explorers (such as Etherscan and Blockchain.com Explorer) allow for manual queries of blocks, transactions, and account information. In addition, many blockchain networks and data providers (such as Etherscan API and CoinGecko API) offer API interfaces to programmatically obtain on-chain data.

Moreover, on-chain data analysis can be mainly divided into two categories: transaction-related and investigative. Transaction-related data analysis can discover early alpha or trends through on-chain data or develop trading strategies by analyzing the fundamental data of trading targets. Investigative data analysis can uncover fund flows, potential address mapping relationships, or find the real reasons behind abnormal events through data correlation.

OKX Web3: On-chain data analysis involves examining and interpreting data directly recorded on the blockchain to gain insights into network activity, user behavior, and market trends. For new users looking to take their first step into on-chain analysis, here are some key points:

First, familiarize yourself with blockchain explorers, such as Etherscan, to understand basic transaction data and wallet activity. Next, pay attention to key on-chain metrics such as active addresses, transaction volume, and supply distribution. Then, explore user-friendly on-chain analysis tools like Nansen, Debank, and Glassnode to visualize on-chain data.

Start with basic metrics, tracking simple data points such as daily active addresses or transaction counts. At the same time, understand how on-chain data relates to market trends and trader behavior, and identify patterns and correlations in price movements by analyzing historical data. Finally, combine on-chain analysis with fundamental and technical analysis to gain a more comprehensive perspective.

2. What key metrics should be focused on?

0xScope: It mainly depends on the needs and scenarios:

If your strategy is fundamental analysis or long-term trading, we recommend focusing on the following 10 metrics:

• Transaction count, which is the total number of transactions occurring on the blockchain network over a period of time, usually reflecting the network's activity and usage;
• Active address count, the number of unique addresses with transaction records over a period of time; the more active addresses, the higher the user participation in the network;
• New address count, referring to the number of new addresses created over a period of time; an increase in new addresses usually indicates that the network is attracting new users, signaling user growth;
• Transaction fees, the total fees paid by users for transactions; high transaction fees may indicate high network demand, reflecting the congestion level of the network and the costs users are willing to pay;
• Average transaction value, the average amount per transaction; a higher average transaction value may indicate more large transactions, helping to understand capital flows and user trading habits;
• Liquidity, the tradable volume of assets in decentralized exchanges (DEX); a market with high liquidity is usually more stable and healthy, affecting trading slippage and market depth;
• Token holding concentration, the distribution of token holders, such as the total holding ratio of the top 10/50/100 holders; high concentration may lead to increased market volatility risk, understanding the concentration of token holdings and market risk;
• Total Value Locked (TVL), the total value locked in DeFi protocols; a high TVL usually indicates that the protocol is popular and widely used, measuring the scale and popularity of DeFi protocols;
• Smart contract call count, the number of calls to smart contracts over a period of time; a high call count indicates that the contract is widely used, reflecting the usage and popularity of smart contracts;
• Developer activity, the frequency of updates to the project's codebase and the number of contributors; high developer activity indicates that the project is continuously improving and developing, reflecting the project's development progress and activity level.

If your strategy is short-term trading or you hope to profit by capturing trends, we recommend focusing on the overbought and oversold conditions in decentralized exchanges, which reflect abnormal fluctuations in current market demand, as well as large deposits or withdrawals from exchanges, which can reveal the potential buying or selling intentions of major players.

If your strategy is copy trading, you can pay more attention to the dynamics of smart money. For example, the historical returns of smart money can help identify traders with strong long-term profitability; trading frequency and volume can inform you about the activity level and market participation of smart money. The success rate of trades assesses the accuracy of smart money's trades, while holding time reveals whether its strategy is short-term or long-term. Asset distribution shows the diversification of its portfolio, and trading fees reflect its trading costs. Risk-adjusted returns measure smart money's ability to generate returns while controlling risk, and the on-chain reputation of smart money reflects its evaluation in the community. Additionally, liquidity supply can help understand whether smart money is also providing liquidity, which may affect its trading behavior. By using these metrics, you can better understand and track the dynamics of smart money.

If you are detecting risks, it is recommended to focus on at least the following 10 key metrics:

• Abnormal transaction count, which refers to the number of transactions significantly higher than normal levels within a specific time frame; this helps identify potential attacks or abnormal activities, such as hacking or fund transfers;
• Large transfers, referring to transactions exceeding a certain monetary threshold, which may indicate asset theft, money laundering, or evasion of detection;
• Transaction frequency, the number of transactions within a unit of time; an abnormally high transaction frequency may indicate ongoing attacks or fraudulent activities;
• Mass transactions from new addresses, where newly created addresses conduct a large number of transactions in a short period; this may be a tactic used by attackers to hide their identity, and observing these addresses can help identify the source of the attack;
• Smart contract calls, involving transaction calls to smart contracts; smart contracts may be the target or tool of an attack, and analyzing these calls can provide insights into the attackers' methods;
• Token transfers, the transfer status of specific tokens within the network; abnormal transfers can indicate specific attacks, such as token theft or illegal transfers;
• Abnormal gas fees, transaction fees that are significantly higher or lower than average; attackers may use high gas fees to accelerate transactions or low gas fees to conceal large numbers of small transactions;
• Transaction time intervals, the time intervals between consecutive transactions; consecutive transactions in a short time may indicate automated attacks or the use of trading scripts;
• Abnormal activities in on-chain protocols and contracts, where specific protocols or smart contracts experience a surge in activity; this may indicate that attackers are exploiting vulnerabilities or that there are internal issues within the protocol;
• Account balance changes, significant changes in account balances; this can help users identify cases of stolen or transferred funds.

Overall, these metrics essentially reflect the traces left by major players in the market. Beginners can analyze these traces to sense market changes.

OKX Web3: For beginners, we recommend focusing on the following four key metrics to gain a deeper understanding of blockchain networks and market dynamics:

• Active address count: This metric provides a basic understanding of network usage and economic activity. By observing changes in active addresses, beginners can understand the actual application level of the network and user participation.
• Transaction volume: Transaction volume is an important metric for assessing market activity, helping to understand buying or selling pressure in the market. High transaction volume usually indicates higher activity among market participants, while low transaction volume may suggest the market is in a wait-and-see state.
• MVRV (Market Value to Realized Value Ratio) and NUPL (Net Unrealized Profit/Loss): These metrics provide profound insights into market valuation and overall sentiment. MVRV can help assess whether the market pricing of a token is reasonable, while NUPL shows whether investors are currently in profit or loss.
• Supply distribution: This metric shows the concentration of token ownership. By analyzing supply distribution, beginners can understand whether tokens are overly concentrated in a few addresses, which may impact market liquidity and stability.

As beginners become more familiar with these basic metrics, they can gradually incorporate other more complex metrics into their analysis, such as on-chain transaction fees, mining difficulty, network hash rate, etc., thereby enhancing their overall understanding of blockchain networks and markets.

3. How to identify emerging Web3 projects through on-chain data?

0xScope: A simple way is to monitor the GAS consumption leaderboard daily; contracts with an abnormal increase often reflect some hot projects from that day or recently.

A more efficient method is to use the Etherscan Chrome GAS plugin, which allows you to see the current GAS level at any time in the upper right corner of your browser. When you notice a spike in GAS, you can use the Top Gas Consumer leaderboard we just mentioned or Etherscan's Gas Tracker to see where everyone's GAS is being spent; usually, in such cases, you can discover some new projects.

A commonly used resource is Scopescan's Top Gas Consumer leaderboard. If you frequently check this leaderboard, you will find that in most cases, the top few on the ETH chain are Uniswap router, USDT contracts, and several TG bots like Banana Gun. If you find an unfamiliar contract on this leaderboard, you can check on Scopescan or Etherscan to see if this contract has a label; for those with stronger hands-on skills, you can also check who deployed this contract and where its fees come from. Another method is to look at the Project Explorer leaderboard on Scopescan; if you suddenly see a project you haven't encountered before appearing on this leaderboard (TVL Rank and User Rank), it indicates that this project is worth checking out.

OKX Web3: In fact, we can identify emerging on-chain projects through various methods. First, monitoring on-chain activity is a crucial step. This includes tracking new smart contract deployments, looking for increased transaction volumes, and unique addresses interacting with contracts. By analyzing the gas usage of new projects, you can gain insights into their activity level and development progress within the blockchain ecosystem.

Secondly, utilizing data aggregation platforms such as Dune Analytics, Nansen, and Glassnode provides customized dashboards that can more effectively track and analyze key metrics of emerging projects. These platforms can not only monitor the growth of total value locked in decentralized finance projects but also track daily active users of dApps and games, and assess the transfer volume and holder growth of new tokens.

In addition to on-chain data, it is also important to pay attention to cross-referencing off-chain data. Monitoring social media activity and community growth, observing developer activity on GitHub repositories, and analyzing the price trends of project tokens and trading volumes on exchanges are all important supplements for assessing the potential of emerging projects. By comprehensively utilizing these methods and data sources, you can better evaluate and identify valuable and promising emerging Web3 projects.

However, if you find it cumbersome, you can also directly check the rankings of DeFi, DEX, and other on-chain protocols in the discovery section of the OKX Web3 wallet, where you can view information such as TVL, DEX trading volume, and lending conditions, which is very convenient.

4. What are the common misconceptions and considerations when conducting on-chain data analysis?

0xScope: We believe that there are several common misconceptions and important considerations to be aware of when conducting on-chain data analysis:

First, a common misunderstanding relates to the interpretation of address labels and activities. For example, transfers do not always represent buying or selling activities, and the deposit and withdrawal activities of exchanges do not necessarily reflect actual buying or selling behavior. Market makers frequently conduct deposits and withdrawals to provide liquidity, so only when these activities are significantly higher than normal levels should they be considered potential market signals.

Secondly, most users typically do not use just one address, so overall activity rather than individual address activity should be considered during analysis. However, smart money may transfer funds through deposit and withdrawal operations on centralized exchanges, meaning that solely relying on on-chain data analysis does not always successfully capture all situations. Additionally, over-reliance on a single data source is risky; it is advisable to combine on-chain data with off-chain data for comprehensive analysis. For instance, when the market experiences sudden fluctuations, understanding possible background news, such as important economic data released by the government, helps provide a more comprehensive market context.

Furthermore, the information or opinions released by KOLs (Key Opinion Leaders) often focus only on specific trading events and do not delve into the underlying addresses and the true situation of entities. Therefore, analysts should independently explore and understand the stories behind the data. Lastly, it is recommended to choose data analysis products with a longer operational history and good reputation to enhance the reliability of the data and the accuracy of the analysis.

OKX Web3: We strongly agree with 0xScope's views. New users conducting on-chain data analysis must pay attention to several common misconceptions and important considerations.

First, the accuracy and reliability of data are crucial. On-chain data may be influenced by various factors, leading to incomplete or inaccurate information. Additionally, be wary of potential data manipulation by project teams or large holders, which may mislead analysis results.

Secondly, a common misunderstanding is the misinterpretation of data. Understanding the context is key when analyzing on-chain metrics, avoiding conclusions based solely on isolated data points while neglecting the overall market situation's impact.

Moreover, over-reliance on a single metric is also a risk. Avoid making decisions based solely on one or two on-chain metrics; instead, use a combination of metrics and cross-reference them with off-chain data to obtain more comprehensive and reliable analysis results.

Finally, be aware that there may be discrepancies between on-chain data and real-world situations. For example, some on-chain activities may not be fully captured, such as off-chain transactions or the impact of layer two solutions. Therefore, understanding the limitations of the data being used is a crucial step for effective analysis.

Conclusion

The above is the fifth issue of the "Insight Data" column launched by OKX, focusing on practical topics such as how beginner players can establish on-chain data analysis methodologies, hoping to provide reference for newcomers. In future series of articles, we will continue to explore more practical data usage/analysis methods to provide reference for traders and new players learning trading and understanding the industry.

Risk Warning and Disclaimer

This article is for reference only. The views expressed in this article are solely those of the author and do not represent the position of OKX. This article does not intend to provide (i) investment advice or recommendations; (ii) offers or solicitations to buy, sell, or hold digital assets; (iii) financial, accounting, legal, or tax advice. We do not guarantee the accuracy, completeness, or usefulness of such information. Holding digital assets (including stablecoins and NFTs) involves high risks and may fluctuate significantly. 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.