Structured Income Research Template for AI and Product Ideas

When you ask an AI or a researcher whether an idea can make money, the worst answers are fluffy: “it depends,” “there is potential,” or “further research is recommended” with no numbers. Those responses waste time. The fix is not better prompting alone — it is a fixed structure that forces concrete outputs. This guide introduces a structured income research template with five mandatory fields and explicit bans on vague language. It works for indie hackers, product managers, and teams that use AI (or humans) to evaluate revenue ideas before building. Why Open-Ended Research Fails Open-ended questions invite open-ended answers. “Can we monetize X?” often produces a narrative without testable claims. You cannot compare two ideas, prioritize a roadmap, or defend a decision to stakeholders without: Named markets — not “everyone who uses apps.” Revenue math — price × volume, ARPU, or RPM with stated assumptions. Feasibility — a scored judgment with reasons, not vibes. Next validation — what