On-Chain Analysis Platform Comparison: Glassnode vs CryptoQuant vs Nansen

A unique benefit of public blockchains is every transaction and address can be viewed and analyzed. Economic data can be analyzed in unprecedented detail in what's called on-chain analysis.

Here are some examples of popular on-chain metrics.

• Liquid supply change - supply in wallet addresses that has not been moved for at least 6 months

• Exchanges net transfer - coins moving on or off exchanges - indicative of available liquidity and market depth (amount needed to move price)

• Coinbase Pro outflows - outflows usually mean movement to cold storage for long term holding, inflows can signal desire to sell, Coinbase Pro is of particular interest because of institutional usage

• Accumulation addresses - Bitcoin addresses that have received at least two transactions but have never spent funds, 'black hole' addresses

• Bitcoin miner net position change - miners net selling or holding new coins

• UTXO realized price distribution - amount of volume traded at each price level, sometimes used to infer resistance levels

The unprecedented transparency is one of the under-appreciated aspects of crypto markets. The information asymmetries we've seen in the stock or precious metals market and economic data are much lower.

Instead of speculating on the status of a commodity squeeze like silver crypto traders can visualize one developing second by second with high precision. You can see if retail (minnows) or institutions (whales) are buying or selling. Whether old OG holders are cashing out or stacking more. Whether network activity is increasing, etc.

In equities this level of data would often only be available if you worked in the company. It's another toolset for people who already use TA and use macroeconomic indicators.

You can access data through Glassnode, Santiment (also has off-chain sentiment data), Cryptoquant, Woobull.

Resources for using on-chain data are Glassnode Academy, Glassnode Insights newsletter, Santiment Youtube channel, on-chain analysts 1 2, and any interview with Willy Woo. This is the best way to learn the context behind each metric.

Analyzing the flows, supply changes, accumulation patterns, etc is helpful in forming and sticking to an investment thesis in an asset class that is notoriously unpredictable, whether your goal is to hold or attempt to trade the cycle top.

It’s remarkable how quickly the network responds to a known vulnerability. "Spend" is a catch all I use on this chart for any Bitcoin movement. It's volume really. PnL is how much the value of every UTXO the last 12 hours has changed since its last move. While the Coldcard Mk3 issue is concerning, the on-chain data shows a massive, coordinated flight to safety over the last 12 hours.

​Compare these two snapshots from my node. The second image shows normal bear-market conditions from 7 days ago... coins in the 1.5 to 8-year age cohorts are characteristically dormant. The first image captures today’s reality: roughly 10,000 BTC moving out of those old cohorts.

​Seeing the community mobilize this effectively to secure funds in real-time is a powerful testament to the resilience of self-custody. Keep verifying and stay vigilant.

For years, I obsessed over candlestick charts, RSI, and moving averages always reacting to price. But I recently shifted my focus to on-chain metrics like active addresses, transaction volume, and developer activity.
What surprised me is how these numbers often start moving before the price does. It’s like getting a quiet heads-up before the market wakes up.
Curious, does anyone else here track on-chain data as part of their market strategy, or is it still too “niche” for most traders?

Hi, I live in Russia and want to move out of here, I don't have any education, I can save up and move to some Russian speaking countries, but I'll probably get stuck, while I am in Russia I have support network so I am self-studying for a few hours every day osint, programming and crypto, because AI(I know stupid, but I don't where else to ask) said that companies in crypto are more willing to hire juniors, plus while in Russia I can only receive payments in crypto, before I move if everything is playing right.

Here's what I would like to ask about(I wrote following text as a message to another person, so I am sorry if I missed some details and something doesn't make sense): 1) How hard is to get junior position on this role? I want work that is remote and will give me enough funds to relocate(I do not expect some golden mountains, AI told me that 1500-2000 usd is reasonable expectations for junior role in this position) 2) Do employers usually expect relevant education, beside self-study knowledge? 3) Can you rate my plan of action? - at the same time I am currently learning progromming(python, data analytics), crypto(honestly somewhat lost for now I am reading up to 2nd chapter of Bitcoin and cryptocurrency and after I will be studying etherscan, arkham and other tools) and osint(for now I have finished cybermentor half of osint course and now I try to practice by doing some small exercises to develop osint mindset, but as soon as crypto knowledge will catch up I will mix crypto and osint practice and later when programming will catch up I will mix all three to build my portfolio in relevant to position aspect) and also AI advised to learn in the later half when I will learn solidly all topics to also learn regulatorics of crypto

Been trying to analyze 3 wallets for the past 3–4 days, but even Claude couldn’t figure them out properly. Would really appreciate help from someone with solid on-chain analysis skills. Drop a comment and I’ll DM the wallets.

Thats interesting where do you get all these stats from? I am new to all this

I’ve tried to do some deep dives before into on chain analysis but found it to be way beyond my capabilities and out my time scope that I have with running a business and having a little one at home.

So I decided to follow guys like Willy Woo and Plan B with there analysis and try use that as a basis of what I think the market might do in the short and long term future.

I tend to find most of there on-chain analysis is quite bullish which I love but I don’t want to be unrealistic.

So I guess does anyone follow these type of guys as a guide of what they see the future of the market looking like or do you literally just study it yourself and make up your own mind?

Cheers legends 🍺

I'll repeat the thread title, "Is On-Chain analysis largely BS?".

The analysts are largely articulate and seemingly intelligent but that's not really pertinent if it's just describing the present with no forecasting validity.

I can describe the present as I'm in the present but so what?

Ciao a tutti, ho analizzato la situazione di AIAO direttamente su BaseScan e volevo condividere alcuni dati positivi che ho riscontrato con laiuto di Gemini:

1. Infrastruttura solida: Il sistema di acquisto su rete Base è velocissimo e i fondi (USDC) arrivano regolarmente ai wallet societari (verificato con TxnHash). L'azienda sta incassando liquidità reale.
2. Riconoscimento tecnico: Il token è già tracciato correttamente nei wallet Web3 di Binance e su CoinMarketCap. Non è un "ghost token".
3. Community in crescita: Gli holder on-chain sono migliaia, il che mette pressione alla società per mantenere le promesse di giugno.

Nota: Sebbene il buyback interno sia stato sostanziamente bloccato, i dati blockchain dicono che l'azienda è operativa e capitalizzata. Restiamo vigili sulla data di giugno, ma i fondamentali tecnici su Base sembrano esserci.

Try taking a look at studio.glassnode.com.

Interesting. How much time delay would you say there is approximately between the on-chain metrics and the impact in the market prices? Are we talking about hours, days, weeks...?

Hi everyone,

I wanted to ask if anyone here does on chain analysis for bitcoin and if you could recommend me some tools to use.

I looked into cryptoquant, coinglass, and glassnode.

I subscribed to glassnode advanced and realized most of the tools that I wanted to use require professional tier which is $833.33 which seems too pricey for me.

Thanks in advance!

Check out Glassnode or CryptoQuant.

Nansen is a great option, expensive tho. As others have said, Glassnode is great as well.

You’re thinking like the top 1% traders do.

The info is good, the data is reliable, but the interpretation is always bullish. Same with the TA guys on youtube; some are really good, have accurate forecasts but always favour the upside and get over excited.

In truth, we don't know what the on-chain indicators mean because they are just now being discovered, and we don't have a lot of data about how those indicators have unfolded in the past.

Nobody knows what will happen in the future. I only use TA and other analytics for confirmation bias

It's a scaling problem. If it's one-hop, one-in-to-two-out, that is easy. But the more hops and the more inputs or outputs the more impossible it becomes. At a certain point it becomes a zebra problem. It is possible to track something, but takes so much effort it just is no longer worth it.

Rather a question of security-through-obscurity, or more precisely privacy-through-obscurity.

Didn't know Claude was good for this stuff? Yeah dm with context

What specifically are you trying to understand about these wallets? The analysis approach varies significantly based on the goal.

If you're trying to trace fund sources or connections between wallets, Solscan and Solana FM show transaction history and you can manually follow the flow. Arkham has some Solana coverage for wallet clustering and entity identification.

If you're evaluating whether wallets are related (same operator, coordinated trading), look at timing patterns, shared funding sources, and whether they interact with the same contracts in similar sequences. This is tedious manual work but the patterns are usually visible.

If you're trying to understand trading behavior or PnL, tools like Birdeye and Step Finance can parse DeFi activity. For pump.fun or memecoin trading specifically, GMGN has wallet profilers.

The reason Claude or any AI struggles with this is that on-chain analysis requires actually querying live blockchain data, which AI doesn't have direct access to. At best it can interpret data you paste in, but the fetching and pattern recognition across transactions is manual work with block explorers and analytics tools.

Happy to point you in a more specific direction if you share what you're actually trying to figure out about these wallets.