Expected output
The deliverable should include Go/No-Go recommendation, Assumption register, Sensitivity analysis, Validation milestones, and Stop criteria.
IntermediateMarket Research & Product Selection AI
Product Selection Validation | Diagnostic Analysis Prompt
Product Selection Validation | Diagnostic Analysis Prompt is a copyable AI prompt for ecommerce sellers. Use it to validate candidate products across demand, unit economics, competition, compliance, and supply chain feasibility from verified business inputs. Copy the full instruction, add your inputs and check the result before use.
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How the Product Selection Validation | Diagnostic Analysis Prompt works
Validate candidate products across demand, unit economics, competition, compliance, and supply chain feasibility from verified business inputs. The prompt identifies data gaps first, ranks findings by evidence strength, and ends with phased actions that require human review.
Key instructions and output
The points below describe the task and expected output in this prompt.
Parameter guide
Prepare the task information listed below and replace placeholders with verified details from the actual case.
[Candidate product]
Replace this placeholder with verified, task-specific information before running the prompt.
[Expected price and cost]
Replace this placeholder with verified, task-specific information before running the prompt.
[Traffic and conversion assumptions]
Replace this placeholder with verified, task-specific information before running the prompt.
[Competitive data]
Replace this placeholder with verified, task-specific information before running the prompt.
[Supplier and compliance information]
Replace this placeholder with verified, task-specific information before running the prompt.
Copy the complete prompt
The complete source is shown below. Copy it from the top right to use it.
You are an ecommerce investment and assortment reviewer. Your objective is to validate candidate products across demand, unit economics, competition, compliance, and supply chain feasibility. Analyze the following real inputs: [Candidate product], [Expected price and cost], [Traffic and conversion assumptions], [Competitive data], [Supplier and compliance information]. First list data gaps and definitions that need confirmation. When information is missing, mark it as 'To be confirmed' rather than guessing. Then provide: (1) key findings and supporting evidence; (2) prioritized root causes or opportunities using impact × evidence strength; (3) Go/No-Go recommendation, Assumption register, Sensitivity analysis, Validation milestones, Stop criteria; (4) executable actions for the next 7, 30, and 90 days; and (5) risks, counterexamples, and assumptions requiring human validation. Special requirement: Do not decide from one optimistic scenario. Include base, downside, and upside cases.Test this prompt on a real task
Copy a starter instruction, add the required inputs, then run one example and review the output.
01Product Selection Validation | Diagnostic Analysis Prompt
The deliverable should include Go/No-Go recommendation, Assumption register, Sensitivity analysis, Validation milestones, and Stop criteria. Diagnose product selection validation issues and prioritize evidence-backed action
Show prompt and variablesHide prompt and variables
Product Selection Validation | Diagnostic Analysis Prompt
The deliverable should include Go/No-Go recommendation, Assumption register, Sensitivity analysis, Validation milestones, and Stop criteria. Diagnose product selection validation issues and prioritize evidence-backed action
You are an ecommerce investment and assortment reviewer. Your objective is to validate candidate products across demand, unit economics, competition, compliance, and supply chain feasibility. Analyze the following real inputs: [Candidate product], [Expected price and cost], [Traffic and conversion assumptions], [Competitive data], [Supplier and compliance information]. First list data gaps and definitions that need confirmation. When information is missing, mark it as 'To be confirmed' rather than guessing. Then provide: (1) key findings and supporting evidence; (2) prioritized root causes or opportunities using impact × evidence strength; (3) Go/No-Go recommendation, Assumption register, Sensitivity analysis, Validation milestones, Stop criteria; (4) executable actions for the next 7, 30, and 90 days; and (5) risks, counterexamples, and assumptions requiring human validation. Special requirement: Do not decide from one optimistic scenario. Include base, downside, and upside cases.Inputs to replace in this prompt
[Candidate product]- Replace this placeholder with verified, task-specific information before running the prompt.
[Expected price and cost]- Replace this placeholder with verified, task-specific information before running the prompt.
[Traffic and conversion assumptions]- Replace this placeholder with verified, task-specific information before running the prompt.
[Competitive data]- Replace this placeholder with verified, task-specific information before running the prompt.
[Supplier and compliance information]- Replace this placeholder with verified, task-specific information before running the prompt.
What to check before using the output
The generated result is a draft; check claims, numbers and operating conditions against source data before publishing, importing or acting on it.
Operating note 1
Replace every placeholder before running the prompt, and label key figures with their source, date range, and definition.
Operating note 2
Do not decide from one optimistic scenario. Include base, downside, and upside cases.
Operating note 3
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.
Source & attribution
Compilation note and reference material
This section identifies the prompt’s creator and source, and marks details that could not be verified.
Vendolune
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.
Reference materialLucky Orange
This link is reference material and does not establish its page author as the author of this Prompt. The article provides ecommerce analysis prompts across strategy, inventory and merchandising, marketing, and customer experience, emphasizing trend detection, competitive gaps, segmentation, and data-backed opportunities.
The original page does not publish a rating, review, Product Hunt upvote, star, fork, install, or download count.
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