You Cannot Improve What You Do Not Measure

A lot of indie makers make product decisions based on feelings.

This page is probably fine. Users must understand the onboarding. I think people are dropping off after signup. This feature is probably the most important one. The landing page should convert better.

Maybe those assumptions are right.

Maybe they are not.

The problem is that without data, every decision feels heavier than it should.

You do not know what to fix first. You do not know where users drop. You do not know which page matters. You do not know which CTA is ignored. You do not know whether people are actually using the feature you spent days building.

So you keep building.

Another section. Another feature. Another redesign. Another pricing test. Another idea.

But the product does not necessarily get better.

It only gets bigger.

This is a common trap for indie makers.

When growth is slow, the instinct is to add more. But sometimes the real issue is not missing features. Sometimes the issue is invisible friction.

Users land on the page but do not click. Users sign up but do not complete onboarding. Users open the app once and never return. Users start a flow but abandon it halfway. Users do not discover the core feature.

Without simple event tracking, you are guessing.

And guessing is expensive.

It costs time. It creates doubt. It makes you change things that may not be broken. It makes you ignore the parts that actually need attention.

But analytics can also become a trap.

Many tools are too complex for early-stage products. They give dashboards full of charts, metrics, filters, and reports before the maker even knows what they need to measure.

That creates a different problem: data overload.

You do not need to track everything.

You need to track the few moments that tell you whether the product is working.

For most early products, that means:

Did people visit the page? Did they click the main CTA? Did they sign up? Did they complete the first key action? Did they come back? Did they use the feature that creates value?

That is enough to start.

Good data does not replace judgment.

It improves it.

It helps you ask better questions. It helps you prioritize fixes. It helps you understand user behavior instead of guessing from silence.

The goal is not to build a complex analytics machine.

The goal is to see the product clearly.

If you are building without knowing what users actually do, you are making decisions in the dark.

BSData helps indie makers set up simple product analytics faster, with practical event ideas, tracking structure, and useful metrics focused on early-stage products.

Start seeing what users actually do here: https://data.project-bs.com