Expected output
The deliverable should include Go/No-Go recommendation, Assumption register, Sensitivity analysis, Validation milestones, and Stop criteria.
Product Selection Validation | Comparative Decision Prompt is a copyable AI prompt for ecommerce sellers. Use it to compare candidate options against one consistent decision framework. Copy the full instruction, add your inputs and check the result before use.
Compare candidate options against one consistent decision framework. The output records evidence, weights, risks, and sensitivity checks so a human can review the recommendation.
The points below describe the task and expected output in this prompt.
The deliverable should include Go/No-Go recommendation, Assumption register, Sensitivity analysis, Validation milestones, and Stop criteria.
Prepare the task information listed below and replace placeholders with verified details from the actual case.
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Replace this placeholder with verified, task-specific information before running the prompt.
Replace this placeholder with verified, task-specific information before running the prompt.
Replace this placeholder with verified, task-specific information before running the prompt.
Replace this placeholder with verified, task-specific information before running the prompt.
Replace this placeholder with verified, task-specific information before running the prompt.
Replace this placeholder with verified, task-specific information before running the prompt.
Replace this placeholder with verified, task-specific information before running the prompt.
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You are an ecommerce investment and assortment reviewer. Compare [Option A], [Option B], and [Option C] for the objective: validate candidate products across demand, unit economics, competition, compliance, and supply chain feasibility. Inputs: [Candidate product], [Expected price and cost], [Traffic and conversion assumptions], [Competitive data], [Supplier and compliance information]. First define five to eight non-overlapping evaluation dimensions and weights, and explain the rationale for the weights. Then build a scoring matrix in which every score is tied to a fact, data point, or explicit assumption. Provide the best choice, conditions under which it is best, irreversible risks, the lowest-cost validation method, and Go/No-Go recommendation, Assumption register, Sensitivity analysis, Validation milestones, Stop criteria. Do not invent missing information to force a conclusion. Special requirement: Do not decide from one optimistic scenario. Include base, downside, and upside cases.Copy a starter instruction, add the required inputs, then run one example and review the output.
The deliverable should include Go/No-Go recommendation, Assumption register, Sensitivity analysis, Validation milestones, and Stop criteria. Compare options and make a reviewable product selection validation decision
You are an ecommerce investment and assortment reviewer. Compare [Option A], [Option B], and [Option C] for the objective: validate candidate products across demand, unit economics, competition, compliance, and supply chain feasibility. Inputs: [Candidate product], [Expected price and cost], [Traffic and conversion assumptions], [Competitive data], [Supplier and compliance information]. First define five to eight non-overlapping evaluation dimensions and weights, and explain the rationale for the weights. Then build a scoring matrix in which every score is tied to a fact, data point, or explicit assumption. Provide the best choice, conditions under which it is best, irreversible risks, the lowest-cost validation method, and Go/No-Go recommendation, Assumption register, Sensitivity analysis, Validation milestones, Stop criteria. Do not invent missing information to force a conclusion. Special requirement: Do not decide from one optimistic scenario. Include base, downside, and upside cases.[Option A][Option B][Option C][Candidate product][Expected price and cost][Traffic and conversion assumptions][Competitive data][Supplier and compliance information]The generated result is a draft; check claims, numbers and operating conditions against source data before publishing, importing or acting on it.
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Do not decide from one optimistic scenario. Include base, downside, and upside cases.
Before uploading order, customer, contract, or supplier data, redact sensitive information and comply with platform terms, privacy policies, NDAs, and company data-governance requirements. Have the responsible operator review the result before it is published, sent, or executed.
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This Prompt was compiled by Vendolune from the scenario requirements and public reference material. The reference-page author is not credited as this Prompt's author.
This link is reference material and does not establish its page author as the author of this Prompt. The author offers executable prompts for small ecommerce businesses and emphasizes specific goals, business context, and clear deliverables such as service surveys, store optimization, and operating efficiency.
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