Product Validation Glossary

The process of identifying which demographic or situational segments experience a problem most acutely — before building the product.

The US Census Bureau's Public Use Microdata Sample — individual-level survey data from the American Community Survey, statistically representative of the US population.

Iterative Proportional Fitting — a statistical method that adjusts sample weights to match known population distributions, ensuring demographic representativeness.

Using multiple AI models to evaluate the same input and averaging results — reducing systematic bias by letting each model's biases cancel out.

The Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism) applied to product evaluation and audience segmentation.

The degree to which a specific audience segment experiences a problem acutely enough to adopt a solution. Evaluates who has the problem, not whether the market wants your product.

A 0–100 metric measuring problem-solution fit per demographic segment. 70–100 = high fit. 40–69 = medium fit. Below 40 = low or minimal fit.

AI-generated representative user profiles grounded in real demographic data — statistically generated from population data, not invented marketing archetypes.