SaaS Analytics: How to Track MRR and the Metrics That Matter

Most indie founders set up SaaS analytics backwards. They wire up a pile of page-view tracking and event dashboards, then have no idea what their actual MRR is or whether they’re churning customers faster than they’re adding them. The metrics that predict whether your SaaS survives aren’t traffic numbers — they’re revenue numbers. This guide covers how to track MRR and the handful of metrics that actually matter, with the free tools to do it.

The trap is measuring everything and understanding nothing. You don’t need a 40-metric dashboard. You need five numbers you check weekly and genuinely understand.

The Five Metrics That Actually Matter

Forget the vanity stuff. For an early-stage SaaS, these are the numbers:

1. MRR (Monthly Recurring Revenue). The total predictable revenue you collect each month from subscriptions. This is your north star — everything else is in service of growing it. Annual plans get normalized to their monthly equivalent (a $149/year plan contributes ~$12.42 to MRR).

2. Churn rate. The percentage of customers (or revenue) you lose each month. For low-touch SaaS the rough benchmarks: under 2% monthly is good, ~5% is acceptable, and above 7% is a flashing warning light. High churn means you have a leaky bucket — pouring in new customers won’t help until you patch it.

3. ARPU (Average Revenue Per User). MRR divided by active customers. Rising ARPU means you’re either pricing better or upselling; falling ARPU means discounting is creeping in.

4. LTV (Lifetime Value). Roughly ARPU divided by your churn rate — how much a customer is worth over their whole relationship. At 5% monthly churn, the average customer stays ~20 months, so LTV ≈ ARPU × 20.

5. Net new MRR. New MRR + expansion MRR − churned MRR. This single number tells you if you’re actually growing this month or just treading water. It’s the most honest growth metric there is.

That’s the whole list for an MVP. Get these right before you touch NRR, CAC payback, or cohort-retention curves.

Why MRR Is Harder to Track Than It Looks

“Just look at your Stripe balance” is the wrong answer, and it’s worth understanding why. Your Stripe payout includes one-time charges, refunds, proration adjustments, and annual upfronts all jumbled together. MRR is a normalized number that smooths annual plans into monthly terms and strips out non-recurring revenue. Calculating it by hand from raw Stripe data is fiddly and easy to get wrong — which is exactly why dedicated tools exist.

The good news for indie founders: the tools that compute this correctly are free at your stage.

Free Tools for Revenue Analytics in 2026

You do not need to build a dashboard or pay for analytics early on:

• ProfitWell / Paddle Metrics — free core metrics (MRR, churn, LTV) with no usage limits. The standard free starting point. It plugs into Stripe and computes the normalized numbers for you.
• ChartMogul — free tier for companies under ~$120K ARR, with unlimited users and proper subscription analytics including cohort and expansion/contraction tracking. Great when you want to go a level deeper than ProfitWell.
• Baremetrics — accurate MRR/churn/LTV pulled straight from your payment processor. Not free, but the gold standard if you want a dead-simple revenue dashboard and you’ve got a few paying customers to justify it.
• Google Looker Studio — fully free if you want to build a custom dashboard pulling from multiple sources. More setup, more flexibility.

The play for a brand-new SaaS: connect ProfitWell to Stripe on day one. It’s free, it computes MRR/churn/ARPU correctly, and you’ll never have to reverse-engineer your Stripe payouts.

Separate Revenue Analytics From Product Analytics

A clarification that saves confusion: there are two different kinds of analytics and they answer different questions.

• Revenue analytics (ProfitWell, ChartMogul, Baremetrics) answer “are we making money and keeping customers?” — MRR, churn, LTV.
• Product analytics (PostHog, Plausible, Mixpanel) answer “what are people doing in the app?” — activation, feature usage, funnels.

Both matter, but at MVP stage revenue analytics come first. You can have beautiful product engagement and still be dying because your churn is 9%. Wire up revenue tracking before you obsess over which button users click. (If you go the product-analytics route, lean toward privacy-first tools like Plausible to sidestep cookie-consent headaches — see our note on this in the GDPR compliance checklist.)

Your Data Is Only as Good as Your Billing

Here’s the part that connects analytics back to engineering: every revenue metric you track is computed from your Stripe subscription data. If your billing integration is leaky — webhooks dropping, subscription state out of sync, failed payments not handled — your metrics lie to you. You’ll think you have 100 active subscribers when 8 of them silently failed their last renewal and you never noticed.

Clean metrics start with a clean billing pipeline. That means webhooks that reliably sync customer.subscription.updated, invoice.payment_succeeded, and invoice.payment_failed into your database, plus proper dunning so failed payments are recovered rather than quietly rotting in your MRR count.

This is exactly the foundation Beag gives you. It wires auth and Stripe billing into your app with the subscription-state syncing and webhook handling already done — so the data your analytics tools read is accurate, and a failed payment shows up as a recovery opportunity instead of a phantom subscriber. Get the billing layer right and your MRR number is one you can actually trust. (For the recovery side specifically, see handling failed payments with Stripe dunning.)

A Weekly Ritual That Beats Any Dashboard

Tools don’t grow your business — paying attention does. The habit that actually moves the needle: every Monday, look at five numbers.

1. What’s my MRR, and is it up or down from last week?
2. What was my net new MRR (new + expansion − churned)?
3. How many customers did I lose, and do I know why?
4. Is ARPU trending up or down?
5. Any failed payments I should be recovering?

That’s a ten-minute ritual that keeps you honest. The founders who make it aren’t the ones with the prettiest dashboards — they’re the ones who actually look, notice churn early, and fix the leak before it sinks them.

Bottom Line

Track five numbers, not fifty: MRR, churn, ARPU, LTV, and net new MRR. Use a free tool like ProfitWell that plugs into Stripe and computes them correctly, so you’re not reverse-engineering payouts. Keep revenue analytics ahead of product analytics at the MVP stage. And remember the numbers are only as honest as your billing pipeline — which is why getting auth and payments wired up cleanly with Beag pays off twice: once in saved build time, and again in metrics you can actually trust. For the full early-stage stack, see our indie hacker tech stack for 2026.

FAQ

What metrics should an indie SaaS founder track?

Five: MRR (monthly recurring revenue), churn rate, ARPU (average revenue per user), LTV (lifetime value), and net new MRR. Get these right before adding more advanced metrics like NRR or CAC payback.

Can’t I just check my Stripe balance for MRR?

No. Your Stripe payout mixes one-time charges, refunds, proration, and annual upfronts. MRR is a normalized number that smooths annual plans to monthly and excludes non-recurring revenue. Use a tool like ProfitWell to compute it correctly.

What’s a good churn rate for SaaS?

For low-touch SaaS: under 2% monthly is good, around 5% is acceptable, and above 7% is a warning sign that you have a retention problem worth fixing before you scale acquisition.

What’s the best free tool to track MRR?

ProfitWell (Paddle Metrics) — free core metrics with no usage limits, connects directly to Stripe. ChartMogul’s free tier (under ~$120K ARR) is great when you want deeper cohort and expansion analytics.

Why are my metrics inaccurate?

Usually a leaky billing pipeline — dropped webhooks, out-of-sync subscription state, or unhandled failed payments inflating your active-subscriber count. Reliable webhook handling and dunning (which a service like Beag provides) keeps the underlying data clean.