pm-hypotheses

To structure product assumptions for validation, you define problem, customer, solution, and market assumptions, then prioritize them by risk and set measurable success criteria to create a structured hypothesis register.

The best way to run customer discovery experiments is to design validation tests like customer interviews and demand tests, track the outcomes, and evaluate the evidence to guide your product development decisions.

To make evidence-based Go or No-Go decisions, you track validation experiment outcomes against measurable success criteria to determine whether the evidence supports moving forward, pivoting, or stopping.

Yes, you can use this approach for startup customer discovery by mapping uncertain ideas into structured problem, customer, and solution assumptions, then prioritizing them by risk to guide validation.

Product teams build on untested assumptions when they lack structured validation frameworks to convert uncertain ideas into measurable experiments and evidence-based Go or No-Go decisions before development.

You should stop or pivot during a product validation experiment when the tracked evidence from your customer discovery tests does not meet the predefined measurable success criteria for moving forward.