GA4 Too Complicated? What Founders Actually Need

Most founders don't need GA4's full event model; they need about ten numbers answered reliably: how many people visit and where they come from, which pages bring them, signups by source, paying customers and revenue by source, one funnel from visit to payment, and a weekly trend. If GA4 makes those hard to see, the problem isn't you. GA4 is designed for teams with an analyst, an ads budget and time to configure reports.

This post lists what a founder should track at each stage, what can be safely ignored, the smallest event plan that answers the questions that matter, and how to decide whether to keep GA4, replace it, or run something simpler alongside it.

Why does GA4 feel so complicated?

Universal Analytics stopped processing data for standard properties on 1 July 2023, and GA4 replaced it with an event-based model built to cover websites and apps, advertising and machine-learning features in one product. That flexibility moves work onto the user. The concepts that trip founders up most:

None of this is a flaw for a marketing team running Google Ads with a dedicated analyst. It is a mismatch for a founder who opens analytics once a week and wants to know whether the newsletter sponsorship worked. The bounce-rate change alone is a common source of confusion; we explain it in what is a good bounce rate for SaaS.

What do founders actually need to track?

Start from the decisions you make, not the data you could collect. Almost every early-stage decision is “where should I spend the next month of effort or money,” which needs these numbers:

That's it for most products until they have a growth team. What changes as you grow is which of these deserve a closer look; the stage-by-stage version is in the SaaS metrics dashboard for indie hackers.

What can you safely ignore?

• Average session duration as a headline number. It is dominated by how your tool treats single-page sessions; look at time on page for content you care about instead.
• Demographics and interests. Estimated, sampled and rarely actionable for a small product.
• Dozens of micro-events. Every click on every element is noise until you have a specific question about a specific page.
• Real-time views as a habit. Useful during a launch; a distraction the rest of the time.
• Multi-touch attribution models before you have a few hundred customers. First touch and last touch are enough to see the shape.
• Pageview totals. Visitors and what they do matter; pageviews mostly measure how many pages your navigation makes people click through.

What is the minimal event plan for a SaaS?

Pageviews and referrers are automatic in every analytics tool. Beyond them, a founder needs a handful of events, each fired at the moment the thing actually happened:

// After the signup API call succeeds (browser)
window.visitrack?.("signup", { method: "email" });

// When the user creates their first project (server)
await fetch("https://visitrack.app/api/track", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.VISITRACK_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({ type: "event", visitorId, name: "activated" }),
});

The code above uses VisitTrack's API, but the plan is tool-agnostic. The important rule is about revenue: take it from your payment provider's webhook, matched to the visitor who paid, rather than from a “purchase” event in the browser. A browser event can be blocked by an ad blocker, double-fired on a page refresh or sent by anyone who opens the console. How the webhook-based approach works is covered in how to track revenue by traffic source.

What does a 15-minute weekly analytics review look like?

1. 1.Visitors this week vs last week and vs four weeks ago, humans only. Note anything over a 20% change.
2. 2.Top five sources by visitors, then the same five by signups. Which one converts, which one just sends traffic?
3. 3.Top five entry pages by signups. Is a new page starting to pull its weight?
4. 4.Payments this week by source. Any new channel showing up?
5. 5.The funnel: visit → signup → activated → paid. Did any step's rate move?
6. 6.Write one sentence: what you'll do differently this week because of what you saw. If there's nothing, that's fine; skip the next review and go build.

If a review takes longer than 15 minutes because you're fighting the tool, that is the real cost of the tool. Some founders now skip the dashboard for routine questions and ask an AI assistant connected to their analytics; asking your analytics in plain English with MCP shows how that works.

Should you keep GA4 or replace it?

The EU consent question deserves its own reading: is Google Analytics legal in the EU covers the current position. Running two tools side by side for a month is cheap and settles arguments; expect visitor counts to differ, because tools filter bots and define sessions differently.

What should a simpler analytics tool give you?

• Sources, campaigns and entry pages on one screen, with bots filtered out by default.
• Signups as a first-class metric, broken down by source and landing page.
• Revenue from your payment provider, attributed to the visitor's source, including refunds.
• A funnel builder that accepts pages and events, with a conversion window.
• A mode that works without cookies, so you can drop the consent banner if you choose to.
• Export and an API, so the data is yours and can feed a spreadsheet.
• Pricing that doesn't gate the features above behind an enterprise plan.

VisitTrack is built around that list: one script tag, signups and funnels, revenue attribution for Stripe, Paddle, Polar, Lemon Squeezy and Razorpay, cookieless mode, and the same features on every plan, priced by monthly events from $5 a month for up to 10,000. The feature-by-feature comparison is on VisitTrack vs Google Analytics. If you can export event-level history from your old tool, it can be imported with original dates, so your charts don't start from zero.

How do you switch without losing your history?

1. 1.Install the new tool next to GA4 and leave both running for at least a month, so you have an overlap period to compare.
2. 2.Recreate only the events from your minimal plan; resist porting every GA4 event you ever configured.
3. 3.Connect your payment provider and check that a test payment shows up attributed to the right source.
4. 4.Export what you want to keep from GA4: monthly totals per channel and top pages are usually enough for trend lines. Event-level history needs the BigQuery export, which only exists from the day it was turned on.
5. 5.Write down the date you switched, and annotate it in any chart that spans it, because visitor counts will differ between tools.
6. 6.Remove GA4 only once nobody has opened it for a few weeks.