Pick the study type that matches what you need to figure out.

It depends on where you are in your work. If you don't yet know what problems your audience cares about, start with problem discovery. If you have hypotheses about specific problems, start with problem validation. If you have a candidate solution, start with concept testing. If your product exists and you're refining how you talk about it, start with value-prop testing. If you're setting or changing a price, start with price testing. Assumption validation can layer on any of these. It's a way to make a study explicitly stress-test the assumptions that matter most to your decision.

Yes. A project is the unit of audience and personas; a study is the unit of research goal. You can build a single audience, generate personas once, and then run a problem-discovery study followed by a concept test with the same personas. They remember the prior conversations, so each subsequent study builds on what they already told you.

Yes. Candor treats B2B and B2C as fundamentally different modeling domains. A procurement lead evaluating enterprise software uses a different decision framework than a consumer making an impulse purchase. When you create a study you choose the audience type, and the entire pipeline adapts: distinct attribute models, personality weightings, bias profiles, and buying triggers for each context.

Both. Pre-launch teams use Candor to test concepts, value props, and prices before they commit to building. Teams with live products use Candor to refine messaging, pressure-test pricing changes, prioritize features, and stress-test the assumptions baked into a roadmap. The use cases are the same; only the timing changes.

No. Candor isn't a replacement for talking to real customers. It's the step before, or the step when traditional research is too slow, too expensive, or not available. Use Candor to generate hypotheses, validate assumptions, pressure-test concepts, and identify which questions are worth spending real research budget on. The best teams use synthetic research to make their real research sharper.