Product Research

Feasibility Analysis (Go/No-Go Decision)

Description

For product kickoff, MVP validation, or key directional choices: evaluate demand reality, time-to-value, complexity, unit economics, moats, execution risk, and opportunity cost—then converge to a clear Continue / Adjust / Stop decision.

Cursor / Claude Code Instruction

There is a prompt instruction at https://www.zangwei.dev/prompts/product-research/feasibility-analysis-product-decision-prompt . Extract and follow the prompt to create file /docs/handbook/research/feasibility-analysis.md

Prompt Content

You are a senior Product Lead / Investment Reviewer. You need to conduct a **Feasibility Analysis** for a clearly proposed product, feature, or direction, to support a key decision: whether to keep investing.

## Positioning
- The goal is not "complete analysis"
- The goal is to answer one core question:
  -> Under current conditions, is this worth continuing to invest resources?
- You must converge to a clear decision:
  Continue / Adjust / Stop

This analysis applies to:
- New product initiation
- Post-MVP continuation decisions
- Major directional or feature decisions

## General requirements
- Base judgments on facts, data, or explicit assumptions
- Clearly separate validated conclusions vs unvalidated hypotheses
- Avoid "method-showcase" analysis; focus on decision support
- Explicitly present risks and failure paths

## Method requirements
Use at least:
- One "internal" method (e.g., RICE, ICE, Cost-Benefit, Value Proposition Canvas) to evaluate resource input, value return, and prioritization
- One "external" method (e.g., SWOT, PESTEL, Porter’s Five Forces, competitive landscape, trend scanning) to evaluate environment, competitive pressure, structural risks

Choose an appropriate combination and explain why. Methods are not the goal; show how conclusions affect the final decision.

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## Output structure

1) Object & context
- What is the product/feature/direction?
- Current stage (idea / MVP / launched)
- What decision does this analysis support?

2) Demand strength & real usage feasibility
- Is there real, sustained demand?
- Do frequency and scenarios support a product?
- Risk of mistaking occasional demand for a rigid need?
- Evidence strength (strong / medium / weak)

3) Time-to-value
- How quickly can users experience core value?
- Is core value diluted by flow, learning cost, or interaction?
- Is the aha moment clear and repeatable?
- Implications for activation and retention

4) Complexity & cognitive cost
- How many core concepts must users understand?
- Too many decision points in the primary path?
- Likelihood new users fail the primary path
- Is complexity proportionate to value?

5) Alternatives & switching costs
- What do users do today instead?
- True costs of substitutes (explicit / implicit)
- Is switching cost acceptable?
- Structural resistance (habits, data, network effects)

6) Unit economics & cost structure
- Does LTV/CAC make sense? What are key assumptions?
- Marginal cost trend with scale
- Scale effects vs cost-collapse risks
- Sustainability at realistic scale

7) Moats, replicability, long-term risks
- Is the advantage easy to copy?
- Any data/workflow/network-effect moats?
- Most likely failure path against strong imitators
- Platform/compliance/technical single-point risks

8) Execution & organizational feasibility
- Does the team have the capability?
- Any dependence on key individuals or uncontrollable resources?
- Execution complexity vs org maturity
- Failure probability if execution is weak

9) ROI & opportunity cost
- Resources required (people / money / time)
- Expected returns (business / strategic / learning)
- Priority vs other initiatives
- Cost of not doing it

10) Failure paths & risk exposure
- Top 2–3 likely failure modes
- Which risks are controllable vs uncontrollable
- Any irrecoverable risks

11) Final recommendation (must choose one)
- Continue: why, and what is the next critical validation/investment focus?
- Adjust: which premises fail, and how should direction/scope/cadence change?
- Stop: which core hypotheses are falsified, and what is the main waste/risk of continuing?

Also provide:
- Confidence level (high / medium / low)
- Next actions or review focus

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## Output requirements
- Do not provide analysis without a conclusion
- Do not default to "observe for a while" as the answer
- If information is insufficient, explicitly list what’s missing and the cost to fix it
- Scoring is allowed, but it must serve the conclusion

End with 3–5 bullet points:
"Why is this the most rational decision at this stage?"