The Best AI Prompt for a Business Feasibility Study

Use a structured feasibility-study prompt to analyze a business idea, market, customers, costs, and risks while separating assumptions from verified evidence.

What AI can do in a feasibility study

AI can organize questions, frame hypotheses, build scenarios, and identify missing data. It does not automatically know current supplier prices, local regulations, or market size. Treat its output as a research draft and validation plan, not final financial approval.

Describe the idea, customer, location, sales model, available resources, and decision you need to make. If the concept is vague, instruct the model to ask questions before analyzing instead of filling gaps with persuasive assumptions.

The complete feasibility-study prompt

You are a business analyst helping me draft a feasibility study, not a financial adviser. Idea: [idea]. Market: [city/country]. Target customer: [description]. Budget and resources: [available]. Start with 10 clarifying questions. After I answer, analyze the problem and value proposition, customer segments, alternatives and competitors, acquisition channels, operations, costs and revenue, regulations requiring verification, and risks. Separate confirmed facts from assumptions and suggest a source or experiment for each assumption. Finish with three scenarios and decision criteria. Do not invent figures or sources.

Run the prompt in stages: problem definition, market, operations, and financial model. This makes assumptions easier to review and prevents one unsupported market-size estimate from distorting the rest of the study.

Test the market, customer, and competition

Map direct competitors, manual alternatives, and doing nothing. Record price, value, and weakness from a recent public source for each alternative. A list of names is not enough; understand why customers use the current solution and what could make them switch.

Turn customer assumptions into interviews and experiments. Ask for open questions, a simple offer page, and a request or waitlist test. Verbal interest is not evidence of payment, so define a success signal such as qualified requests or actual reservations in advance.

Build a three-scenario financial model

Separate startup from monthly costs and fixed from variable costs. Define the sales unit, price, delivery cost, and volume. Request explicit formulas, then move them into a spreadsheet and change the assumptions yourself rather than trusting a final total.

Create conservative, base, and optimistic cases, then test sensitivity to price, demand, and cost. Verify taxes, fees, permits, and licensing with the relevant authorities. Consult a qualified accountant or adviser when the decision creates significant financial or legal obligations.

Turn the study into a decision and small experiment

Request a decision matrix covering problem strength, demand evidence, operating ability, unit economics, risk, and time to first customer. Attach evidence and confidence to every score, and do not let an average hide a decisive risk such as a missing license.

The best outcome is not a long report but a low-cost action that reduces the largest uncertainty: interviews, a quote, prototype, or limited sales test. Feed real results back into the analysis and record how they changed the original assumptions.