Why conversion feels “exact”?

Conversion rates are often treated like facts. 2.4% vs 2.6% — and suddenly budgets move. I’ve seen teams fight over noise.

What everyone forgets?

Conversion is an estimate.

  • Small samples lie
  • Randomness exists
  • Not every change is real

Without uncertainty, decisions become dangerous.

What BigQuery quietly allows?

If you know successes and sample size, you can estimate uncertainty. No magic, just math.

How to use it in practice? Try not to show conversion alone:

  • Conversion rate
  • Lower and upper bounds
  • And only then — interpretation

It saves money and reputations.

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