Which metrics matter most in a zero-to-one product?

Example Answer

In a zero-to-one product, I would use metrics to answer one question first: are users getting enough value to come back? That usually means focusing on activation, time to first value, repeat behavior, and qualitative evidence that the product is solving a real problem. I would avoid over-optimizing vanity metrics early, because volume without value can hide that the core experience is still weak.

I would pair the numbers with direct user conversations so I know whether low performance is a discoverability issue, a product-market fit issue, or an execution issue. Early-stage PM work is less about building a perfect dashboard and more about using a small set of honest signals to decide what to learn next.

Why this works

• It picks the right early-stage metrics instead of defaulting to big top-line numbers.
• It combines data with qualitative learning.
• It shows that the purpose of metrics is deciding what to learn and build next.