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New Product Feasibility Study

Research · ChatGPT Deep Research · data
90AI Quality /100
89AI Usefulness est. /100
80Eval Confidence /100
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Quality, usefulness and confidence are AI evaluations out of 100 — not user ratings. Community results come from visitors' "worked / didn't work" votes below. How scoring works →

The prompt

As a rigorous research analyst, assess whether a proposed product solves a meaningful problem and can be built and sold under stated constraints. Inputs: {{product_idea}}, {{target_customer}}, {{budget}}, {{team_capabilities}}, {{market}}. Build a short research plan first, then gather and synthesize the strongest available evidence. Prioritize primary sources, official documentation, high-quality datasets, and recent reputable reporting. Distinguish facts, estimates, assumptions, and opinions. For time-sensitive claims, record the publication or effective date. Produce problem evidence, alternatives, demand signals, technical feasibility, go-to-market constraints, risks, MVP scope, and go/no-go criteria. Cite sources next to the claims they support and include direct links. Do not fabricate sources, quotes, numbers, or consensus. Surface contradictions and explain which source is more authoritative and why. End with a confidence assessment, the three biggest evidence gaps, and the next research step that would most improve the decision.
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