The blockchain can present you that one thing occurred, however it gained’t inform you why or who was behind it, or whether or not it’s really actual demand. A sudden spike in addresses might imply real customers are piling in. Or it might simply be Sybil farmers taking part in the system. An uptick in TVL might sign contemporary capital coming in, or it would simply be the identical collateral getting wrapped, restaked, bridged, and counted a number of occasions. A surge in transactions might level to actual utility or it could possibly be a bot, a factors marketing campaign, an arbitrage loop, or a contract design that forces customers to leap by means of ten steps simply to do what one other chain handles in one.
At ChangeNOW, we have a look at blockchain knowledge on daily basis, however we don’t deal with it as a scoreboard as a result of we all know that on-chain metrics are sometimes mechanically correct however analytically deceptive.
Under are 5 on-chain metrics that usually mislead the market and a greater solution to learn every one.
- The Most Quoted Metric in Crypto, and One of many Best to Misinterpret: Lively Addresses
In conventional product analytics, you normally have a person tied to an account, a tool, an electronic mail, a subscription, some type of persistent identification. On-chain, although, an tackle is only a public key. One particular person can simply management dozens of wallets. One pockets can signify a number of individuals. A sensible contract can generate exercise that appears user-like. And a centralized alternate can funnel funds for hundreds of shoppers by means of only a handful of addresses.
Even the definition of an “energetic tackle” is broader than most individuals understand. Coin Metrics, for example, counts any distinctive tackle that’s both sending or receiving ledger adjustments, and that features mining, staking, common transactions, account creation, and different chain-specific occasions. On some networks, the accounting construction makes issues even messier.
In its 2024 State of Crypto report, a16z famous that month-to-month energetic crypto addresses hit 220 million in September 2024 however in addition they made some extent of warning that energetic addresses are a lot simpler to recreation than different metrics. In a later estimate, they put the actual variety of month-to-month transacting crypto customers someplace between 30 and 60 million, which is barely about 14% to 27% of that 220 million headline determine.
Caption: Lively addresses are a helpful sign, however they don’t seem to be the identical factor as customers. One human can management many wallets; one pockets can signify many individuals; and bots or Sybil farmers can inflate the depend.
A greater metric isn’t uncooked energetic addresses, it’s quality-adjusted energetic customers. Which means addresses or clusters that present repeated, economically significant habits over time.
2. The Metric That Confuses Dimension With Well being: TVL
TVL is one in every of DeFi’s favourite metrics as a result of it’s easy. It takes an entire difficult system and compresses it into one headline quantity — how a lot worth is locked up. The factor is, TVL can embrace idle capital, mercenary liquidity, incentive-seeking deposits, recursive collateral, wrapped belongings, liquid staking tokens, liquid restaking tokens, bridged belongings, and belongings whose actual exit liquidity is far thinner.
Educational work has change into more and more important of TVL as a standalone metric. A 2024 paper, Piercing the Veil of TVL: DeFi Reappraised, argues that TVL could be inflated by means of double-counting actions corresponding to wrapping and leveraging. The authors suggest “Whole Worth Redeemable” as a extra dependable various and estimate that at DeFi’s 2021 peak, the hole between TVL and redeemable worth reached $139.87 billion, with a TVL-to-TVR ratio of roughly 2.
A separate 2025 examine on TVL verifiability discovered that TVL computation is usually not standardized and should depend on self-reported or non-transparent strategies. In a case examine of 400 protocols, the authors’ verifiable TVL estimates aligned with revealed figures for under 46.5% of protocols. So TVL could be actual and nonetheless not imply what individuals suppose it means.
3. Exercise Is Not the Similar as Utility: Transaction Rely
A series with low charges can generate huge transaction counts from bots, video games, spam, failed makes an attempt, arbitrage, NFT minting, token approvals, reward claims, or sensible contract designs that require a number of steps per person motion. One other chain could course of fewer transactions however signify higher-value, higher-intent habits.
If one person motion requires eight on-chain transactions, the dashboard could present eight models of “exercise.” The person skilled one activity. Or worse, one irritating activity.
That is particularly necessary in cross-chain habits. A person who desires to maneuver worth from Asset A to Asset B could contact a pockets, a bridge, a gasoline token, an approval transaction, a swap, a declare, and a destination-chain transaction. If the route is fragmented, the transaction depend rises. However the person expertise could also be worse, not higher.
A transaction graph may also be dominated by infrastructure actors. A 2024 examine of Polkadot’s transaction ecosystem discovered that exchanges owned practically 40% of all addresses within the ledger and absorbed at the least 80% of all transactions, with excessive inter-exchange transaction quantity elevating questions on how a lot exercise mirrored end-user adoption.
It reveals why transaction counts want actor classification.
So a greater metric is intent completion charge. Which means asking:
Did the person full the swap?
Did the route carry out as anticipated?
Did they return?
Did they select the identical asset or ecosystem once more?
Did failures cluster round a particular chain, token, liquidity supply, or pockets sort?
4. The Metric Most Prone to Look Spectacular Whereas Saying Very Little: Quantity
Quantity could be one of many dirtiest metrics in crypto. NFT markets gave the business one of many clearest examples. Chainalysis has described NFT wash buying and selling as transactions the place the vendor is successfully on either side of the commerce, making a deceptive image of worth and liquidity. In its 2022 crypto crime analysis, Chainalysis recognized NFT wash buying and selling as a major abuse sample and defined how self-funded tackle relationships can be utilized to detect suspicious trades.
Any market the place the identical actor can commerce with themselves, recycle funds, or generate quantity to qualify for rewards can produce deceptive exercise. Quantity additionally must be separated by goal.
There’s a big distinction between:
- a person swapping ETH to USDC as a result of they want steady liquidity;
- an arbitrage bot shifting between swimming pools;
- a market maker rebalancing stock;
- a CEX shifting funds internally;
- a farmer producing quantity for a factors marketing campaign;
- a wash dealer creating the looks of demand.
All of those can present up as quantity. Just some signify sturdy person demand.
So the extra helpful metric is quality-adjusted quantity. Which means discounting quantity that seems round, incentive-driven, bot-heavy, or operational slightly than user-driven. It additionally means weighting quantity by completion, repeat habits, liquidity high quality, and help price.
Caption: Uncooked quantity tells you that worth moved. High quality-adjusted quantity asks whether or not that motion got here from sturdy person intent.
5. Progress or Simply Disposable Identification? New Addresses
New addresses are sometimes handled as the highest of the adoption funnel. Extra new wallets means extra new customers, proper? Not essentially.
A brand new tackle generally is a new particular person. It will probably additionally be:
- an present person rotating wallets for privateness;
- a farmer creating a whole bunch of wallets;
- a bot deployment;
- a sensible contract pockets;
- a CEX-generated tackle;
- a one-time bridge tackle;
- a pockets created solely to assert, mint, check, or far
In crypto, identification is reasonable. That’s each a function and an analytics nightmare. Because of this “new addresses” must be handled as a cohort, not a conclusion.
The Higher Framework:
The problem isn’t that on-chain metrics are unhealthy. The problem is that most individuals learn them too actually.
A great product analytics framework ought to transfer by means of 4 layers.
Caption: A metric turns into helpful solely when it strikes from uncooked blockchain exercise to a product determination: what to help, enhance, prioritize, or ignore.
That is the core distinction between market analytics and product analytics. Market analytics typically asks: “What’s trending?”. Product analytics asks: “What habits ought to we construct for?”
Inside ChangeNOW, on-chain analytics is most helpful when it’s related to product actuality. A public dashboard could present {that a} chain is heating up. That may inform us the place to research. However earlier than treating it as a product alternative, we need to perceive whether or not the sign survives contact with precise person habits.
This type of evaluation is much less flashy, however it’s a lot nearer to the reality.
Correlation Isn’t Causation: The 5 Most Deceptive Metrics in On-Chain Analytics was initially revealed in The Capital on Medium, the place individuals are persevering with the dialog by highlighting and responding to this story.
