Token KPIs: 12 Examples and a Framework for Crypto Teams

Token KPIs are the handful of metrics a crypto team uses to decide whether its token, protocol and incentives are actually working. Not LLM tokens, not API spend: onchain usage, retention, holder concentration, fees and risk, each tied to a decision. This guide gives you a working definition, 12 token KPI examples with the companion metric each one needs, a one-page KPI template, and the validation checks I run before any number reaches a dashboard.

TL;DR:

• Answer a decision. A token KPI should answer a decision, not decorate an investor update. Write the decision first, then the metric.
• Keep the system small. Use 8 to 12 KPIs across four questions: is it used, does it return, who creates the value, and what does the protocol earn or risk.
• Pair every headline. Every headline KPI needs a companion metric that shows its fragility. TVL needs concentration, volume needs repeat users, holders need address labels.
• Check who drives the number. Morpho's migration feature showed $38.5M migrated, but Ethereum's $6.4M came from just 70 transactions. The headline hid that only whales had adopted it.
• Validate before reporting. Validate the event, the decimals and the joins before a number becomes a KPI, and document what would make it wrong.

What are token KPIs?

Token KPIs are key performance indicators that measure how a crypto token and the protocol around it create, retain and capture value onchain. They combine usage metrics (swaps, deposits, borrows), behavioural metrics (cohort retention), distribution metrics (holder and liquidity concentration) and economic metrics (fees, incentive cost, bad debt).

They are not the same as tokenomics. Tokenomics is the design: supply, emissions, vesting, utility. Token KPIs are the measurement that tells you whether that design is producing the behaviour you wanted. A tokenomics model says emissions should attract sticky liquidity. A token KPI tells you how much of that liquidity is still there 60 days after rewards drop.

It is also a niche skill set. On October 26, 2026, only 4 of the 459 live data roles on the Unchain Data job board mentioned tokenomics, while 41 mentioned retention and 95 mentioned A/B testing or experimentation. Teams hire for measurement discipline first, and token context second, which is also what we see when we hire crypto data analysts for clients.

Start with the decision

Most token KPI decks begin with the dashboard. That is backwards.

Start with the decision the number is supposed to change. Are we deciding whether liquidity incentives are working, whether a launch should move to another chain, whether governance participation is real, or where the roadmap should focus? Each question needs a different measurement model.

I have seen teams track TVL, active wallets, volume and token holders because they are available. None of those figures is useless. The problem begins when they are treated as proof of product health without checking what is underneath them.

12 token KPI examples, grouped by the question they answer

I group a token KPI system around four questions. The table below is the set I start from with protocol teams, then cut down to what the next decisions actually need.

Question	Token KPI	Companion metric that exposes fragility
Is the product being used?	Value-bearing actions per week (swaps, deposits, borrows, LP adds)	Share of actions from contracts and aggregators vs direct wallets
Is the product being used?	Active wallets with at least one value-bearing action	Median actions per active wallet
Is the product being used?	Volume or deposits in USD	Volume from the top 10 wallets as a share of total
Is that behaviour returning?	Week-4 and week-12 cohort retention, anchored on the first value-bearing action	Retained value per cohort, not only retained wallets
Is that behaviour returning?	Retention of incentivised cohorts vs organic cohorts	Activity in the 30 days after rewards end
Who is creating the value?	Holder concentration (top 10 and top 100 share of supply)	Same figure after labelling exchanges, staking contracts, bridges and treasuries
Who is creating the value?	LP or depositor concentration (share of TVL from the top 1% of wallets)	TVL that would remain if the top 10 providers left
Who is creating the value?	Governance participation (voting power used per proposal)	Share of that voting power from the top 5 voters and from team or treasury wallets
What is the protocol earning?	Protocol fees and revenue	Fees per unit of incentive spent
What is the protocol earning?	Market utilization (borrowed over supplied, per market)	Utilization at the rate kink and time spent above it
What is the protocol risking?	Liquidations and outstanding bad debt	Recovered value vs protocol loss per liquidation event
What is the protocol risking?	Open interest and funding (for perps)	Liquidation volume relative to insurance fund balance

You will not need all twelve. A lending protocol, a DEX and an infrastructure token should not share a north-star metric. The point is to make the trade-off visible enough that product, growth and treasury decisions share the same factual base.

Several of these KPIs are tracked in public dashboards I built, so you can see the definitions in practice: holder distribution and supply in Morpho's GMorpho dashboard, per-market utilization in the Navi verified lending dashboard, liquidations and bad debt in the Suilend historical record, and open interest, funding and insurance fund balance in the Bluefin perps record. More examples live on the Dune dashboards page.

A headline metric can hide the real risk

In an anonymous liquidity analysis, fewer than 1% of LP wallets controlled roughly 82% of cohort TVL. A dashboard that reported stable total liquidity without showing concentration would have implied a resilience the protocol did not have.

The same pattern showed up in public data at Morpho. In October 2024, the migration feature that moved positions from Aave and Compound had brought in $38,478,978. That looked like a success. Split by chain and by transaction, it told a different story:

Chain	Liquidity migrated	Migration transactions	Average per transaction
Base	$32,123,783	8,223	about $3,900
Ethereum	$6,355,194	70	about $90,800

Ethereum adoption was a few large positions, not a product that retail users had found. Funnel tracking then showed why: the migrate button had near-zero engagement because it was dark on a gray background. After a visibility fix and a frontend redesign, Ethereum migrations grew 433%, from about $6M to about $32M by January. The full story is in the Morpho migration case study.

That changes the leadership conversation. The relevant question is no longer only whether TVL or migrated liquidity increased. It is whether the value is broad enough to survive a small group of sophisticated participants changing strategy.

How to read holder concentration without fooling yourself

Holder concentration is the token KPI most often misread. A top-10 share of 90% can mean insiders control the token, or it can mean the top of the list is an exchange hot wallet, a staking contract, a bridge escrow and a treasury multisig.

Before you report it:

1. Label the top addresses. Separate exchanges, staking and vesting contracts, bridges, treasuries and market makers from independent holders.
2. Report both versions. Raw concentration and concentration after excluding labelled custody and protocol contracts.
3. Pair it with float. Concentrated supply plus a thin float means a small number of decisions can move price far more than the circulating supply suggests.
4. Treat labels as hypotheses. One owner can hold across many wallets, and public labels are sometimes wrong. Note the confidence next to the number.

Use a one-page KPI template

The most useful thing a token team can produce is not a dashboard. It is a one-page definition for each KPI that anyone can challenge. This is the template I use:

Field	What to write
KPI name	One unambiguous name, for example Week-4 retained depositors
Decision it informs	The budget, roadmap or risk decision that changes if this number moves
Definition and formula	Numerator, denominator, time window, chain scope
Source tables and filters	Exact tables, contract addresses, excluded wallets (contracts, team, market makers)
Companion metric	The metric that shows when the headline is fragile
Owner	One person accountable for the definition and its changes
Invariants	Checks that must hold, such as supply reconciliation or balances never going negative
Known limitations	Wallet identity gaps, attribution confidence, missing chains
Review cadence	Weekly, monthly or per decision cycle

If your team runs OKRs, this template slots directly into key results. I cover that link in Web3 OKRs: What They Are and Why Protocols Need Them, and the broader metric hierarchy in the Crypto KPI Framework for Web3 Teams.

Validate the event before it reaches the KPI

The most expensive dashboard errors start upstream. A decoded event changes, a token decimal is handled incorrectly, or a query silently doubles a join. The chart still renders, so the mistake survives.

That is why I treat invariants as part of the KPI definition. In a recent public indexing project, I encoded checks such as supply reconciliation and zero-tolerance balance differences before relying on the downstream numbers. When an invariant fails, the answer is not to explain away the chart. It is to stop and find the broken assumption.

Token reporting needs the same standard. Record the source tables, filters, time boundaries, owners and known limitations next to each KPI. A metric is much more useful when somebody can explain what would make it wrong. The Blockchain Data Audit Checklist lists the checks I run first.

Measure incentives like an investment

Incentives can produce impressive short-term graphs. They can also buy activity that does not return once the reward changes.

For every incentive or partner campaign, compare the acquired cohort with an organic cohort on retained behaviour, retained economic value and cost. Then look at the period after the incentive falls. If the activity disappears, that is not necessarily a failed program. It is a cost and product decision that should be visible before the next budget is approved. How to Measure Protocol Retention Right covers the cohort mechanics, and How to Measure Onchain Growth Correctly covers separating real growth from incentive noise.

The best token KPI systems make that discussion easier. They do not claim certainty where wallet identity and attribution are incomplete. They state the confidence level, show the segments, and provide a decision-grade view of what to do next.

Where to track token KPIs

• Public KPIs (holders, supply, TVL, fees, utilization): a public Dune dashboard, so investors and the community can fork and verify every number. See Dune Dashboards for Investors: What Actually Matters.
• Internal KPIs (cohorts, incentive ROI, segment value): a private Dune workspace or your own warehouse, joined to product analytics when the question involves your frontend.
• Definitions and ownership: the one-page template above, kept next to the dashboard, not in someone's head.

If you need token KPIs that connect onchain behaviour to product and growth decisions, Unchain Data can build the model and the reporting layer, starting with a one-week Web3 data strategy audit or a full Web3 OKR strategy.

Frequently Asked Questions

What are token KPIs?

Token KPIs are the metrics a crypto team uses to judge whether its token and protocol create, retain and capture value onchain. They usually cover usage (value-bearing actions, active wallets), retention (cohorts), distribution (holder and liquidity concentration) and economics (fees, incentive cost, bad debt), each tied to a specific decision.

What are examples of token KPIs?

Common examples are weekly value-bearing actions, active wallets, week-4 cohort retention, holder concentration, share of TVL from the top 1% of wallets, governance voting power used, protocol fees per unit of incentive, market utilization, liquidations and bad debt, and open interest with funding for perps. Each should come with a companion metric that shows when the headline is fragile.

How do you measure token holder concentration?

Calculate the share of supply held by the top 10 and top 100 addresses, then recalculate after labelling and excluding exchanges, staking and vesting contracts, bridges and treasuries. Report both numbers, pair them with float, and note the confidence of the address labels.

What is the difference between tokenomics and token KPIs?

Tokenomics is the design of a token: supply, emissions, vesting and utility. Token KPIs measure whether that design produces the intended behaviour, such as retained liquidity after emissions fall or broad governance participation.

How many token KPIs should a crypto team track?

Track 8 to 12 at most, spread across usage, retention, value creation and economics or risk. Each KPI should have one owner, one decision it informs and one companion metric. Anything that informs no decision belongs in an exploratory dashboard, not the KPI set.

Which tools are used to track token KPIs?

Dune is the most common choice for public token KPIs because every query can be forked and verified. Internal KPIs often move to a private Dune workspace or a data warehouse, joined with product analytics tools such as PostHog, Mixpanel or Matomo when frontend behaviour matters.

Key Takeaways

• Write the decision first. A token KPI that informs no decision is decoration.
• Keep a small system of 8 to 12 KPIs across usage, retention, value creation and economics or risk.
• Pair every headline with a companion metric. Morpho's $6.4M of Ethereum migrations came from 70 transactions, which a single liquidity number would have hidden.
• Label addresses before reporting holder concentration, and show both raw and adjusted figures.
• Document each KPI on one page: definition, sources, owner, invariants and known limitations.
• Judge incentives on retained value after rewards end, not on the launch spike.

Get your token KPIs audited by Unchain Data →