assumption-testing

Product viability testing involves mapping value, feasibility, and viability assumptions, then prioritizing them by risk to design efficient validation experiments. This approach addresses development risks early and informs pivot decisions before committing significant engineering resources.

Prioritize product assumptions by evaluating both their potential impact and level of uncertainty. High-impact, high-uncertainty assumptions are tested first through structured risk assessment to prevent costly development mistakes and guide pivot decisions.

Testing willingness to pay requires mapping the subscription assumption as a viability risk and designing a market test experiment. This validation method targets the specific revenue assumption to efficiently gather evidence before scaling development.

Yes, assumption testing evaluates technical feasibility risks like backend scalability by mapping them to technical spikes. This validates whether chosen technologies can handle expected loads before you invest in full-scale implementation.

Use user research to validate value assumptions about user behavior and needs, and technical spikes to assess feasibility risks like architecture constraints. Matching validation methods to assumption types ensures efficient product risk assessment and actionable results.