The fact that blockchain transaction data is publicly available makes it possible to use it to analyze the behavior of other users on the network. Specifically, for onchain analysis.
➡️ Onchain analysis is the analytics of data found in an open-source blockchain. In other words, the dynamics of everything going on behind the scenes of crypto projects.
Onchain data allows you to see exactly: who owns what, what transactions are made, etc. All this information is stored in blocks or transaction records.
➡️ Examples of on-chain analysis metrics:
1) Transaction volume.
A metric that measures the total number of transactions that occurred on the blockchain over a certain period of time. It is used to evaluate the level of activity in the network.
2) Analysis of smart money (behavior of big players).
Venture capital funds or whales (owners of large amounts of capital in their wallets) can act as a big player. Due to the large amounts of funds, they are able to influence the price of this or that asset. Also, to some extent, they can foresee future trends and narratives in the market.
3) Development activity.
A measure of development activity, measured by the number of "events". Shows how many actions developers take. Increase in developer productivity may show that the project is preparing any updates or innovations.
4) Number of active addresses/users.
This metric shows the number of addresses that made at least one transaction within a certain time. If the number of active addresses is high, it indicates that the project has a strong user base.
There are a large number of such metrics. Which one you should use depends on your analysis purposes.
↪️ Services for on-chain analytics:
• Nansen (https://www.nansen.ai/)
• Glassnode (https://glassnode.com/)
• Dune (https://dune.com/browse/dashboards)
• Token Terminal
(https://tokenterminal.com/)
Have you ever used on-chain analysis?
👍 - Yes
👎 - No
