A SaaS startup usually needs three kinds of analytics, not one: what users do inside the product, how visitors reach the marketing site, and what billing data says about revenue. Pick one tool per job, keep the stack small, and agree early which source gives the number you report.
It's Monday, and three numbers are on the screen. Product analytics says active users went up. The website tool says trial sign-ups went down. The billing dashboard says monthly recurring revenue is flat. Someone asks which one is right, and the honest answer is all of them, because each is counting a different thing.
That's the problem this list is built around. It's for founders and early product or growth leads who need a small stack they can trust, not a wall of dashboards. Five of the nine are built for, or widely used by, SaaS teams, and I've said which. The website tools are general, and I've labelled them that way too. They're in no particular order, because the right tool depends on which job you're filling.
Three jobs that count in three different ways
Product analytics counts events: a click, a page view in the app, a feature used. Website analytics counts visits and sources on your marketing pages. Billing tools count money: subscriptions started, upgraded, cancelled. Those are three separate measurements, and they rarely sit well in one tool.
Because they're counted differently, they won't reconcile. A user can show as active in product analytics while their subscription has already lapsed in billing. A sign-up can appear on the website tool and never reach the product at all. That isn't a bug in any of them. It's why a startup should pick one tool per job and agree, early and in writing, which source is the number you put in front of investors and the team.
One more check while you're at it: some website tools say they don't need a cookie banner. That's the vendor's claim, and consent rules vary by country, so check what applies to you with your regulator or adviser.
Which tool covers which job
What users do inside the product
Amplitude is product analytics with AI across analytics, feedback and code, and a stated free start. Mixpanel pairs product analytics with session replay, experiments and feature flags. PostHog is an open product platform that suits engineer-led teams, and our list of other open product platforms compares it with similar tools. Heap, from Contentsquare, aims to record the full range of user behaviour on site and app. Userpilot ties usage and adoption analytics to in-app onboarding, which suits a product-led SaaS team. If you're stuck between two of these, our head-to-head of the two best-known product analytics tools goes deeper.
How visitors reach the marketing site
Plausible and Fathom are general website analytics tools, not built for SaaS specifically, and both pitch light, privacy-focused scripts. They're for the marketing site, not the app. If you also want to see where visitors click and scroll, our round-up of heatmap tools covers that.
What the billing data says about revenue
The two revenue tools here are both built for subscription businesses. ChartMogul focuses on recurring revenue metrics such as MRR, churn and revenue per customer. Baremetrics works with Stripe and adds retention, forecasting and cancellation insights. These are the tools that answer the question your investors ask first.
The nine at a glance
| Tool | Job it covers | What it brings to a startup |
|---|---|---|
| Amplitude | Product analytics | Product analytics with a stated free start |
| Baremetrics | Revenue analytics | Stripe-billed startups tracking subscription health |
| ChartMogul | Revenue analytics | Recurring revenue reporting from billing data |
| Fathom | Website analytics | Cookie-free traffic numbers for a marketing site |
| Heap | Behaviour analytics | Seeing everything users do on site and app |
| Mixpanel | Product analytics | Replays, experiments and analytics together |
| Plausible | Website analytics | Lightweight, open source site analytics |
| PostHog | Product platform | Engineer-led teams wanting one product platform |
| Userpilot | Analytics plus onboarding | Usage analytics tied to in-app onboarding |
Nine analytics tools for early SaaS teams, in no particular order
Amplitude
Best for: Teams wanting product analytics with AI across analytics, feedback and code; the vendor states a free start, as of Nov 2026.
Baremetrics
Best for: Stripe-based startups that want MRR, retention, churn and forecasting, with cancellation insights the vendor lists as part of the product.
ChartMogul
Best for: Founders who need recurring revenue metrics such as MRR, churn and revenue per customer, pulled from billing data into subscription reports.
Fathom
Best for: Marketing site traffic without cookies, using a fast script, for founders who want a simple view of where visitors come from.
Heap
Best for: Product teams that want a wide record of user behaviour across a site and app, from Contentsquare's digital insights platform.
Mixpanel
Best for: Early teams that want product analytics alongside session replay, experiments and feature flags in one platform rather than four tools.
Plausible
Best for: Lightweight, open source website analytics hosted in the EU; the vendor says no cookie banner is required, and a free trial is stated as of Nov 2026.
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PostHog
Best for: Engineer-led startups that want an open product platform; the vendor says it diagnoses problems, fixes bugs and generates pull requests.
Userpilot
Best for: Product-led SaaS teams building in-app onboarding without code, with usage, feature adoption and funnel analytics in the same tool.
Questions to settle before you install anything
- Who'll own tracking? Product analytics only works if someone names events consistently. Decide who that is before you add a single line of code.
- Which number is the headline? Pick the source for active users, sign-ups and revenue now, and write it down, so the Monday meeting stops arguing about whose dashboard is right.
- Where does your billing live? Revenue tools connect to billing systems. Check that yours is supported before you shortlist one.
- What do your consent rules require? Cookie and tracking rules vary by country. Check yours before you rely on any vendor's claim about banners.
- What will you drop? Every extra tool is another script and another login. If two tools overlap, keep one. For a wider view of the product side, see our list of product analytics tools.
Plain advice for founders
Don't start with the most capable product analytics tool you can find. Start with the question you need answered this quarter. If it's whether people stick after sign-up, you need product analytics and a short list of named events. If it's where sign-ups come from, a simple website tool will tell you. If it's whether the business is growing, a billing-based revenue tool will tell you faster than any event dashboard.
Keep it to one tool per job, and resist adding a fourth until the first three are trusted. I'd rather see a startup with three tools that everyone believes than eight that nobody does. And when the numbers disagree, which they will, don't try to force them to match. Agree which one you report and explain the others.
What a small starter stack looks like
For most early SaaS teams, a sensible first stack is one product analytics tool, one website analytics tool and one revenue tool connected to billing. That's three logins, three scripts or connections, and three clear owners.
If your team is engineer-led and happy with a broad platform, one product tool can stretch across more of the product side. If you're product-led and onboarding is where users drop off, analytics tied to onboarding may earn its place first. Whatever the mix, review it after your first few months of real users, and cut anything nobody's opened in a month.
Do you make an analytics tool for SaaS startups? Tool makers can ask to be considered for a featured place on this list.
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Frequently asked questions
What analytics does an early SaaS startup need?
Usually three kinds: product analytics for what users do in the app, website analytics for how visitors find you, and revenue analytics from billing data. One tool per job keeps the stack small and clear.
Why don't my product analytics and billing numbers match?
They count different things. Product tools count events and active users, while billing tools count subscriptions and revenue. Pick one source for each headline number and explain the gap rather than forcing them to match.
Do I need product analytics before launch?
Light tracking on a few key events helps from the first users, as long as someone owns the event names. A full setup can wait until you know which actions predict that users stay.
Is website analytics enough for a SaaS startup?
It tells you how people reach your marketing site and sign up, but not what they do inside the product or whether they keep paying. Most startups add product and revenue analytics as users arrive.
Do privacy-focused analytics tools remove the need for a cookie banner?
Some vendors say so, but that's their claim and consent rules vary by country. Check what applies to your business with the regulator or your adviser before you remove a banner.
Should a startup use one all-in-one analytics platform?
A broad platform can cover a lot of the product side, which suits engineer-led teams. Revenue reporting from billing data is usually still a separate job, so check what the platform covers before you rely on it alone.
