Learn how to analyze on-chain crypto data to better understand transaction patterns, perform fundamental analysis and identify trends in the crypto ecosystem.
Unlike traditional banking infrastructure, blockchain-based digital ledgers are publicly visible and easily audited.
Dozens of platforms now extract, analyze and visualize on-chain data for easy use, ensuring users are more informed than ever before and can trade on an equal playing field with data-savvy funds.
Why Analyze On-Chain Data?
On-chain analysis is the examination of blockchain data to understand transaction patterns, asset movements, and network health, aiding stakeholders in making better-informed decisions within the cryptocurrency space.
Users will tend to analyze on-chain data for one (or more) of the following reasons:
- Fundamental Analysis: By measuring data points like token holder counts, trading volume and decentralization metrics, users can assess the intrinsic value and potential of a cryptocurrency or project.
- Risk Management: Analyzing transaction behaviors, potential vulnerabilities and liquidity patterns helps users understand potential threats and assess the safety of their investments.
- Auditing: On-chain data ensures the verification of transaction records and that funds and contract actions are transparent and traceable, allowing for accurate and comprehensive audits.
- Trend Analysis: It can be possible to discern emerging patterns in blockchain activity over time. By observing these patterns, stakeholders can predict potential future behaviors, gauge the momentum of specific assets or platforms, and make informed decisions aligned with the evolving blockchain landscape.
How To Analyze Popular Blockchain Data Points
As the blockchain landscape becomes more diverse and competition between platforms and protocols increases, developers have found ways to extract and analyze dozens of different on-chain data points.
These data points now underlie the trading and risk management decisions of thousands of individuals, businesses and institutions around the world. And it’s now possible to get to grips with this data without a degree in computer science or in-depth knowledge of blockchain technology.
Here, we take a look at how you can access some of the more useful data points:
Total-Value Locked
Active Addresses
As you might have guessed, active addresses are a measure of the number of addresses that are active on a specific network within a given timeframe — typically 1 day, 1 week or 1 month.
Changes in the number of active addresses can indicate whether a blockchain is growing or declining in adoption and utility. Likewise, changes in the average transaction size and average holdings per address can indicate changes in user demographics.
Token Holder Counts
Imagine if you could see exactly how many wallets were holding a specific token at any given time, and easily track how this number changes with time — or based on events, updates or market conditions.
From here, you’ll typically see a field describing the change in token holders over time. DexScan also provides a breakdown of the largest holders, allowing you to monitor their activity.
Revenue
One rapidly growing measure of blockchain and independent protocol health is blockchain and protocol revenue.
This is a measure of the amount of revenue generated by a platform or protocol and can be formed from a range of different sources, such as transaction fees, staking rewards, burned coins/tokens, payments and more.
It is generally agreed that projects with a high revenue-to-fee ratio are in a more economically favorable position than those with a low one — this is doubly important during periods of stagnation.
Transaction Volume
In the race to establish the fastest blockchain with the highest possible throughput, dozens of approaches have now been explored. Some believe that by measuring the number of transactions these chains process on average relative to their maximum throughput, it is possible to determine which chain is gaining dominance.
Others use transaction volume data for more practical purposes — such as avoiding transaction congestion, spotting anomalous behavior or gas minimization.
It’s important to note that it is generally not advisable to directly compare absolute transaction counts across different blockchains, since some blockchains may be subject to spam transactions, voting transactions and junk transactions that can inflate this figure.
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