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, these on-chain data are interpreted as signals that Ethereum’s fundamentals are strengthening.
On the 8th (local time), on-chain data analysis firm CryptoQuant pointed out in its latest report that Ethereum’s 7-day average number of transactions has reached 870,000. Compared to about 600,000 transactions at the end of December last year, this is an increase of nearly 45%. This is not a short-term spike but a structural increase in trading activity, indicating that actual usage within the network is rising.
Especially since December 29 of last year, the number of transactions once soared to a daily high of 1.06 million. Although there was some adjustment afterward, it has recently stabilized at a high level around 900,000 transactions for several weeks. The report analyzes this by stating, “This is not a one-time event or temporary speculative demand, but rather a broadening user base and solidification of network usage are forming.”
The increase in on-chain activity is driven by the overall vibrancy of the Ethereum ecosystem, including DeFi, NFTs, and decentralized applications. Unlike mere price fluctuations, data such as transaction counts are indicators of actual demand, especially during periods of price consolidation, making their value more prominent.
If the growth in transaction volume can be sustained long-term, it could serve as a positive signal for the market. Since using protocols on Ethereum requires paying Gas fees in ETH, increased on-chain demand implies a broader actual demand for ETH. Historically, this pattern often foreshadows subsequent price rebounds.
Currently, Ethereum is seeking direction around the $3,200 (approximately 4.656 million KRW) level. If this rise in on-chain indicators is not a one-off event but a forming trend, it is expected to lay a crucial foundation for the upcoming bull market.
💡 “The truth told by numbers, on-chain data does not lie”
The 45% surge in Ethereum transaction count is a signal of actual network demand growth rather than short-term price fluctuations. The ability to read and interpret such signals is the strength of on-chain analysis.
In the second phase of TokenPost Academy: Analyst Course, you will learn how to distinguish and interpret “meaningful indicators,” rather than simple figures like transaction volume.
On-chain indicator analysis: Practical case studies on transforming market psychology into time series data using MVRV, NUPL, SOPR, and more
Tokenomics analysis: Structural analysis of how the growth in transaction counts impacts token prices
Develop the ability to judge “why prices are rising and when they might fall,” rather than just saying “I heard it’s going up a lot.” Start your growth journey now at TokenPost Academy.
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Course system: A 7-stage practical masterclass from basics to on-chain analysis and investment strategies
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TP AI Notes
This article uses a language model based on TokenPost.ai for summarization. The main content of the body may be omitted or may differ from actual facts.