10 Web3 Project Metrics To Help Drive Growth

web2 and web3 have many differences, but they also share quite a few similarities from their early days. Most notably is the need to transition from surface level, or sometimes vanity metrics, to metrics that are core to the fundamental success of a project.

While big number metrics like tracking unique visits, or unique wallets, has some value, it’s missing the more important part of the story. The important part of the story is who your users are, and how healthy your project, or company, actually is.

Understanding who your users are, beyond the surface level, is critical to just about every aspect of what you may do because every project is in some form going to need to:

  • Create an awesome product to help your users
  • Have great marketing to attract, acquire, and retain your users
  • Build a roadmap of features
  • Collaborate or partner with other projects

While the list goes on, one thing is true — you can’t do any of the above effectively without understanding who your users are, and how it relates to the health of your project. Web2 had this same need. The good news is there are about 9 core metrics that emerged over time to be guiding stats in web2 around this, and as a result, are equally important in web3.

10 Core Metrics to web3 projects

We’re going to dive into each of the 10 core metrics and how to use them to better your project. With the below, we are skipping over metrics such as Token Price, and TVL. There will most certainly be additional metrics to these 10 that are important to a project, but I wanted to start with a base set of metrics every project should care about.

New Wallets

New Wallets are those users whose first on-chain interaction with your project happened in a particular period of time. The reason why tracking “first on-chain interaction” is so important is because it shows the first time they actually “converted”, or became a customer.

New Wallets are going to show you part of the conversion step in your growth process, highlighting acquisition. In web3, there’s actually two aspects to consider before the conversion itself happens:

  1. How many views your conversion page is getting
  2. How many times a user has connected a wallet

Wallet connections are also a very valuable metric to track, as it gives you insight into your potential web3 conversion rate.

Think about it this way: If you get 1,000 views and of those, only 25 connect their wallet, that means only 2.5% even started to potentially convert.

Let’s then say that of those 25 that connected their wallet, only 3 actually transacted on chain. That would mean a 12% conversion rate of those who connect a wallet. Those 3 users that actually transacted are now in your “New Wallet” category.

The question should then be, what’s unique about those 3 users that converted? Do they use similar dApps? Did they come from the same marketing source? Are they part of your community? There’s plenty more to dig into here that can help drive growth.

If you’re not tracking wallet connections along with new wallets, definitely reach out to us. It’s why we made an easy to install snippet to help.

Active Wallets

Active wallets are those that have been consistently active with your project within a particular window of time.

The definition is going to look different for different projects. For some this may be as simple as saying they’ve interacted with your project in the last 30 days. For others it may be a longer window of time and the inclusion of a governance token. I’d generally keep it around 30 days though, toward an idea of Monthly Active Wallets (MAW).

Regardless of how you define it, the importance of tracking Active Wallets is critical as it’s one of your strongest indications of market traction within a segment. If you consider the chart above, for instance, many folks view the relatively flat line as a negative. On the contrary, I’d say it’s usually quite positive as it means you’ve found a consistent set of users. Digging into habits of these consistent users should give you a good indication of how to grow your user base.

The above, for instance, is an example of digging into what kinds of personas your active users may be. One other thing I find very effective is putting my Active Wallets into segments like super user, high value, and competitive user. It’s particularly helpful setting these up in Raleon, because I can then do deeper analytics in each segment as well.

At Risk Wallets & Saved Wallets

At Risk wallets are those users that have not been active with your project within a particular window of time, usually within the last 30–60 days. While uncomfortable, At Risk Wallets give you a good indication of:

  1. Lack of market fit
  2. Lack of features necessary to keep users
  3. Targeting non-ideal customers (this is very common)

Alongside “At Risk Wallets” are “Saved Wallets”. Saved Wallets are those that at one point were at risk, but are now back in the active category. Saved wallets can be a great indication of:

  1. New or existing features that now match ideal customer demand
  2. Market fit improvement
  3. Effective communication channels to reach existing customers

In the case of the above two charts, what we’re seeing is a little concerning because we don’t see particular movement in the number of Saved Wallets.

Dormant Wallets & Recovered Wallets

Dormant Wallets are wallets that have not been active with your project within a particular period of time, usually more than 90 days. Dormant Wallets are your indication of a lost customer. The only reason we don’t call them “lost” is because there is still a chance to recover them — as you can see in the chart above.

Recovered Wallets are those wallets that were once Dormant, but have since been moved back into an active state. A wallet that has been recovered usually helps give good indications of lifetime value, different kinds of segments your users may fall into, as well as indications of your non-ideal customers.

When I do analysis on dormant wallets, while there is a lot of valuable information, I find one key data point in particular helpful: where did they go? The reason this is so helpful is it gives you a good indication of ideal customers or not.

This chart does not show all the possible categories of activity

Let’s take a look at the above chart as an example. Let’s say you’re an NFT Marketplace. If you had a wallet use you for the last 3 months, then go dormant for 3 months, that may not be a bad thing. If you check their wallet profile in Raleon, for instance, you might see they were last active on-chain (regardless of project) 2 months ago.

If, however, you see the majority of wallets that go dormant are going to another NFT Marketplace — in this case an aggregator — that could mean you haven’t nailed your product or that they’re not really the kind of NFT user you want.

Ultimately you’re going to have users that go dormant. It’s the nature of any project or business. The question is at what rate does a user go dormant? Or stated differently, what is your retention?

Retention Rate

Retention Rate tells you, of the customers you have today, how many you are going to keep. It’s the inverse of churn, which tells you how many customers you may lose. Retention, in my opinion, is one of the killer metrics.


If your retention rate is great, then it gives you a lot of opportunity. Marketing is more effective, you get more user feedback, and features tend to drive more impact.

Retention combined with the other metrics we’ve talked about give you great intel about your customers and your project. A consistently active user base with a high retention rate, for example, informs you that you have a strong set of customers.

Customer Lifetime Value (CLTV)


What the lifetime value calculation looks like for web3 is going to depend on the project. Below is a pretty common CLV in the web2 world that I think can work as a solid baseline for web3.

CLV = (Average Purchase Value × Average Purchase Frequency × Customer Lifespan)

The easy way to calculate Customer Lifespan with the above is to take your total customer lifespan, and divide it by your total number of customers.

What this starts to get you to is an indication of your business health. The simple math is if your CLV is greater than your cost to acquire your customer (CAC), you’re at least trending in the right direction.

Ecosystem Lifetime Value (ELTV)

Web3 brings a new paradigm to the importance of ecosystems, hence the beginning of what I would call an ecosystem lifetime value. Ecosystems are often the lifeblood of a project — whether it’s a highly active community member, big holders of a collection, whiles providing liquidity, and the list goes on.

What’s important to note with ELTV is that none of the above roles may be heavy users of the product directly. For example, I might not play a game very often (low CLTV) but I may play a vital role in the ecosystem as a market maker. In this scenario, you would want to be able to understand my ELTV against my LTV to make sure the appropriate attention is being given.

While we can help with measuring ELTV, there is not yet a perfect formula. The factors we consider are:

  • Governance involvement
  • Community involvement
  • Financial involvement (NFT holding, or being a liquidity provider)

Overall I can see a scenario in which a community members CLTV and ELTV are combined to get a more full perspective of their value.

Customer Acquisition Cost

As you might suspect, Customer Acquisition Cost (CAC), is the cost of acquiring a new customer. It’s an important metric to consider when evaluating both the methods of acquiring customers and the channels.

In web3, for example, airdrops are effectively web3 native CAC. Tomasz Tunguz has a great breakdown of web2 CAC vs web3 CAC focused on airdrops. It shows that web3 CAC via an airdrop is about 3–7x higher than web2, but depending on project phase and CLV, that may not be a bad thing (and it may change over time).

The other consideration with CAC are the channels you can use to acquire new customers. I generally like to evaluate my CAC, and CLV, on a per channel basis. Below is a list of some of the ways project have acquired customers:

What you find over time is that the conversion rate, CLV, and CAC is going to differ across different channels and activities on those channels. If you’re asking how you track some of these details across channels that are web2, you’re not the only one. Many projects we’ve spoken with say they’re flying blind when it comes to connecting off-chain with on-chain results. That’s part of why we created our off-chain event stream for Raleon.

How Do I Get Started Tracking These On-Chain & Off-Chain Project Analytics?

You may be wondering — if these metrics are so important, why aren’t more projects tracking them? The same reason they weren’t tracked earlier in web2. It was very hard and costly to do.

As a result, only the projects that could afford to hack together a solution, or build it internally, could get this kind of information. Not to mention the challenge of blending the valuable web2 data into the mix.

Without the right data, it’s difficult to understand your project’s health, make great product decisions, and perform effective marketing so you can consistently grow.

Use Raleon to Start Understanding And Engaging Your Users

Whether you use us to help with this or not — these are metrics that will be invaluable to you. We’ve designed our solution to be no-code, specifically for marketing, business development, and product people at projects. We do also have projects that use our API to enrich their data, for the more code oriented.

If you’re interested in getting started, reach out to us to get early access to Raleon and join our community!

The great news about all this is, with the ability to have these metrics at your fingertips, you can then start to move into the next most important step: using the data to engage your users. We’ll talk about that in a future article.

TL;DR Web3 Project Metric Cheat Sheet

While we went in-depth on all these, here’s a handy TL;DR web3 project analytics cheat sheet.

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