How we wrote this. We have not run these seven tools on client sites, and we have not benchmarked them. The descriptions below come from each vendor’s public documentation and from how the tools are commonly used. Treat this as a shortlist to test, not as a verdict.
Web3 teams that move off Google Analytics usually end up with a small stack: one tool for website traffic, one for product events, and one way to join on-chain actions to off-chain sources. This page covers seven options that fit those jobs. For each one you get the question it answers and the trade-offs to check before you commit.
Quick Answers – Jump to Section
- Why do Web3 teams move off Google Analytics?
- What should a Web3 analytics stack answer?
- PostHog: product events and funnels
- Mixpanel: retention and cohorts
- Amplitude: journeys and behaviour paths
- Matomo: privacy-first website tracking
- Plausible: simple, cookie-free web analytics
- Fathom: simple reporting with strong privacy defaults
- A wallet and on-chain attribution layer
- How can you test these tools yourself in two weeks?
- Frequently asked questions
Why do Web3 teams move off Google Analytics?
Web3 users rarely follow a straight path, and that is the main reason teams look for another tool. A person might read your docs on a phone, connect a wallet on a desktop, and finish the action inside a dApp browser. Google Analytics records the page views, but the wallet steps need custom events to show up, and the join between devices is weak.
Privacy is the second reason. If you have users in the EU, consent banners and data handling add work, and some teams would rather measure with tools built around privacy from the start.
There is also a newer reason. More people now arrive from AI answers and summaries, and some of them never click through. If you want to measure what happens after those visits, start with how to get found when nobody clicks, then decide which tool can show you the rest.
For a wider look at why dashboards mislead, see why marketing reports lie in Web3.
What should a Web3 analytics stack answer?
A Web3 analytics stack should answer three questions: where users come from, where they drop out, and whether they come back. Each question needs a different kind of tool, which is why one product rarely covers everything.
Start with the events that mark progress in a Web3 product:
- Wallet connect
- Chain switch
- Signature request
- Transaction submitted
- Transaction confirmed
- First value moment, such as a first swap, deposit or stake
Log the same events every week, with the same names. Consistent naming is what lets you compare one month with the next. If you need a short list of on-chain numbers to pair with these events, the on-chain metrics VCs watch are a useful starting point.
PostHog: product events and funnels
PostHog is a product analytics platform built around events, funnels and session replay, and it can be self-hosted or used as a cloud service. That makes it a common first choice for teams that want to see exactly where users drop out of a flow.
For a Web3 product, the useful part is instrumenting steps such as “clicked connect”, “signed message” and “transaction confirmed”, then watching how the funnel changes after you ship a new onboarding flow. If wallet drop-off is your problem, steps to cut wallet onboarding drop-off map directly onto PostHog funnels.
Check before you commit: it needs more setup than a simple web analytics tool, and the value depends on how disciplined your event naming is.
Mixpanel: retention and cohorts
Mixpanel is a product analytics tool known for event tracking, funnels, retention and cohort analysis. A cohort is a group of users who did the same thing in the same period, which lets you ask what happens to people who did X in week one by week four.
In Web3, that might mean users who bridged once, or users who staked within 24 hours of connecting. Comparing cohorts by chain, source or onboarding path gives you a way to pick one change, ship it and measure the result.
Check before you commit: pricing and limits are based on event volume, so estimate your monthly events before you choose a plan.
Amplitude: journeys and behaviour paths
Amplitude is a product analytics tool that includes journey and pathing views, which show the routes users take through a product. That suits Web3 because people move between docs, dashboards and wallets, and often need several attempts to finish a transaction.
It is built for questions such as “what do users do right before they stop coming back?” and “which feature brings them back?”. It can also show which paths begin with an educational page and end with money moving.
Check before you commit: like Mixpanel, it works best when your events are clean, so audit your event list before you import data.
Matomo: privacy-first website tracking
Matomo is an open-source web analytics platform that you can self-host or use as a cloud service. Teams with strict compliance needs choose it because they can keep the data on infrastructure they control.
For Web3 brands with EU users, data handling is part of the job. If you are already working through checks such as AML and sanctions screening, your measurement setup should be just as defensible. The EU compliance checks Web3 projects face are a useful reference.
Check before you commit: Matomo can run without cookies, but it has to be configured that way. Confirm your settings in the browser before you assume that no consent banner is needed.
Plausible: simple, cookie-free web analytics
Plausible is a lightweight web analytics tool that says it uses no cookies and collects no personal data. It is open source, with a self-hosted option and a paid cloud service.
It gives a clean view of pages, sources and countries, and it lets you track goals. It is not a product analytics tool and does not try to be one. Many teams pair it with PostHog or Mixpanel, using Plausible for content decisions and the product tool for what happens inside the app.
Check before you commit: the feature set is deliberately small, so check that goals and custom events cover the actions you need.
Fathom: simple reporting with strong privacy defaults
Fathom is a hosted web analytics service with a privacy-first design that also says it does not use cookies. It sits in the same simple-analytics group as Plausible and is chosen by teams that want clean reporting without a heavy setup.
The practical benefit is a quick read on which content works, which sources bring real users and which pages are dead weight. You can then fix or merge the weak pages instead of adding more content.
Check before you commit: it is a hosted service, so self-hosting is not the standard route. If you need your data on your own servers, look at Matomo or Plausible’s self-hosted option instead.
A wallet and on-chain attribution layer
This is the question teams ask about this part of the stack: how do you track users when wallets are anonymous? You do not track people the way Web2 did. You track actions and sessions, and you tie them to a wallet address only when the user chooses to connect.
In practice, that means a simple event pipeline. Log wallet connect and transaction events, then join them to off-chain sources such as UTM tags, referrers and email clicks. Treat the wallet steps as part of the product and not as a marketing afterthought. Users also worry about wallet security, which is why how AI agents protect Web3 wallets is worth reading before you design the flow.
Check before you commit: data protection authorities in Europe have said that blockchain data can count as personal data in some situations, so take legal advice on what you store and join.
How can you test these tools yourself in two weeks?
Pick two candidates, one for web traffic and one for product events, and run them side by side on a single funnel for two weeks. Do not try to replace everything at once.
- Define five events. For example: page view, wallet connect, signature request, transaction confirmed and first value moment.
- Install both tools. Keep Google Analytics running in parallel so you can compare.
- Compare against your own data. Check wallet connect events in the tool against the connections you can see on your own back end or on chain. Large gaps tell you where a tool is losing data.
- Check consent behaviour. Open the browser’s developer tools and confirm which cookies and storage each tool sets.
- Check page speed. Compare load times with and without the script.
- Price it at your volume. Estimate your monthly events or page views and check the plan cost.
Write down the result of each step. If you run this test, we would like to hear what you find.
Frequently asked questions
What is the best Google Analytics replacement for Web3?
There is no single best tool, because the options do different jobs. For website traffic, teams often consider Matomo, Plausible or Fathom. For product events and funnels, PostHog is a common starting point.
Can I track wallets in analytics tools?
You can track wallet-related events, and you can link them to a wallet address only after a user connects. Before that, you are tracking sessions and actions.
What events should a Web3 dApp track?
Start with wallet connect, chain switch, signature request, transaction submitted, transaction confirmed and a first value moment, such as a swap or deposit.
How do I measure retention in a Web3 product?
Use cohorts based on meaningful actions, such as a first deposit or first stake. Then check what share of each cohort returns in week one, week four and week eight.
Do I still need web analytics if I have product analytics?
Yes. Web analytics shows which content and channels bring users, and product analytics shows what those users do after they arrive.
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