Dune Dashboards for Investors: What Actually Matters

TL;DR:

• An investor dashboard should explain quality, drivers and risk, not decorate a protocol narrative.
• Wallet counts and TVL require methodology, entity context and clear exclusions.
• The first screen should answer the protocol's current health in under a minute.
• Good reporting exposes uncomfortable concentration before it becomes a surprise.

A dashboard should make the story harder to fake

The test of an investor dashboard is not whether it has the right charts. It is whether a fund, founder or operator can see what is really happening without a ten-minute explanation.

In a private analysis for a Solana concentrated-liquidity DEX, I looked at the top 100 pools and started with a leadership question: who actually controls the liquidity, how concentrated is it, and what risk does that create?

The initial wallet view looked more diversified than the underlying economic reality. After entity attribution, fewer than 1% of LP wallets controlled roughly 82% of the cohort's TVL. More than 18 addresses mapped to one automated-vault counterparty. Several pools depended almost entirely on that one entity.

That is exactly why investor reporting cannot stop at TVL and wallet counts. The analysis informed product-launch, roadmap and resource-priority decisions, then became an ongoing monitoring and alerting system. The protocol stays anonymous, but the lesson is broadly useful: a number can be accurate at the address level and still misleading for a capital-risk decision.

Start with the question an investor is trying to answer

A dashboard for a lending protocol should not look like one for an AMM or an infra network. Begin with the decision, then work backward to metric definitions.

Investor question	Better evidence than a headline chart
Is growth durable?	Retained wallets, repeat action, fee quality, cohort behaviour
Is liquidity healthy?	Net flows, concentration, utilization, in-range capital, dependency by pool or chain
Is revenue meaningful?	Gross fees, rebates, emissions, treasury accrual and the economic definition used
What can break?	Counterparty concentration, bridge exposure, incentives, contract and chain dependencies

The top layer should be deliberately small. A reader should understand the current operating state in under a minute: the core user or capital metric, economic output, an important trend, and the largest risk.

Show the methodology beside the metric

Onchain data is public, but the business definition is not automatic. If a chart says active wallets, explain the qualifying action and exclusions. If it says revenue, say whether that means gross fees, net treasury accrual or tokenholder value capture. If it says TVL, state whether it includes bridged assets, LP positions or double-counting.

This is not defensive documentation. It is what lets the dashboard survive diligence and internal challenge. Dune makes logic inspectable, which is a strength when the query structure and definitions are treated as part of the product.

Organize the dashboard in three layers

1. Executive health

Use only the metrics that define the business now. For an AMM, that may be retained liquidity, volume that creates fees, active LPs and net flow. For a lending protocol, utilization, supplied and borrowed capital, revenue and borrower cohorts may matter more.

2. Drivers

Break the headline metric into the factors that explain it. Show chain mix, pool or vault mix, incentives, cohorts, asset composition, and whether growth is broad or concentrated. This is where a claim such as "TVL is up" becomes a useful answer rather than a status update.

3. Risk

Make the risks visible before a reader has to ask. Top-entity dependency, out-of-range liquidity, one-sided flows, bridge reliance and high exposure to a single asset or incentive program all belong here when relevant.

Common investor-dashboard failures

The most common failure is cumulative charts without a current-state view. Nearly every cumulative line rises over a long enough period. That does not establish momentum.

The next is confusing wallets with independent users or counterparties. In the LP analysis, address-level counting masked a material dependency. The right answer was not to delete the wallet chart. It was to add entity logic and state the confidence of the mapping.

The last is combining internal operations and investor reporting in a single crowded dashboard. Internal users need diagnostic details. Investors need a concise decision layer with drill-downs only when something warrants attention.

When Dune is enough

Dune is an excellent starting point when the critical questions are onchain and the definitions are well governed. Public queries also give investors and communities a way to verify the methodology instead of accepting a private spreadsheet.

It is not the whole reporting stack when the business depends on product funnels, acquisition data, CRM context or finance reconciliation. In that case, Dune should anchor the onchain truth while a broader data model connects it to the rest of the operating system.

Build for the decision, then monitor it

The private liquidity analysis did not end as a presentation. It became a dashboard and alerting process because the question continued to matter after the initial review. That is the standard for investor reporting: it should produce a metric a team watches, understands and acts on, not a screenshot created for the next update.

For dashboards built around decisions rather than vanity metrics, see Unchain Data's Dune Dashboard service.

Frequently asked questions

Which metrics belong on an investor Dune dashboard?

Start with the protocol's actual business model: activity, economic output, capital behaviour and risk. A lending dashboard may emphasize utilization and bad debt, while an AMM should show fee quality, liquidity composition and concentration. Every headline metric needs a clear definition and drill-down.

Why are wallet counts risky in investor reporting?

Wallets are observable, but they do not always equal independent people or counterparties. One entity can control many addresses. When concentration affects a product, treasury or liquidity decision, add a transparent entity layer instead of treating raw wallet count as a measure of diversification.

Should investor reporting be public?

Public onchain dashboards can build trust when the logic is clear and the information is appropriate to share. Sensitive operational analysis can remain private. The important distinction is not public versus private, but whether the metric definitions are stable, documented and decision-ready.