Structured Income Research Template for AI and Product Ideas
This article introduces a structured income research template with five mandatory fields to evaluate revenue ideas before building. It helps avoid open-ended, vague responses and produces concrete, testable claims.
Why it matters
This template provides a systematic way to evaluate revenue potential of product ideas, which is crucial for indie hackers, product managers, and teams using AI to make informed decisions.
Key Points
- 1The template includes fields for scheme name, target market, estimated revenue, technical feasibility, and validation plan
- 2It bans the use of hedge words, revenue conclusions without math, and recommendations for more research
- 3The template can be used with AI assistants to keep the model within guardrails and produce comparable, auditable answers
Details
The article argues that open-ended questions about monetizing ideas often lead to vague, unhelpful responses. The structured income research template aims to fix this by requiring specific details on the target market, revenue estimates with calculation logic, technical feasibility scoring, and a concrete validation plan. This turns the research into a checklist artifact that can be compared, tracked over time, and fed into planning tools or AI agents. The template is designed to be used with AI assistants, where the model is prompted to fill out the template with explicit assumptions if data is missing. Adopting this structured approach can help teams make more informed, data-driven decisions about which ideas to pursue.
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