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A rigorous prompt kit for wine brand analysis

Learn how to create comprehensive prompt kits for wine brand analysis that ensure answer accuracy, policy consistency, and transaction readiness across ChatGPT, Perplexity, and Google AI.

eLLMo Team
eLLMo Team
•15 min read
AI CommerceAgentic CommerceBest PracticesWine IndustryTechnical Guides

The challenge every winery faces

Your winery's brand appears in AI answers across ChatGPT, Google AI, and Perplexity. But are those answers accurate? Do they reflect your actual shipping policies? Can customers actually complete a purchase based on what AI assistants tell them?

Many wineries discover too late that AI assistants are sharing outdated vintages, incorrect pricing, or policy information that doesn't match reality. This isn't just a technical problem. It's a revenue problem. Every inaccurate answer is a missed sale. Every policy misstatement risks customer trust and compliance issues.

This guide provides a comprehensive prompt kit designed for wine brand analysis across three critical workflows: Baseline Assessment, Content Optimization, and Customer Insight Mining. These prompts align with eLLMo AI's framework emphasizing answer accuracy, policy consistency, and transaction readiness. They're copy-paste ready for ChatGPT, Perplexity, and Google AI, and come equipped with scoring rubrics, data capture schemas, safety guardrails, and evaluator instructions.

What this prompt kit delivers

Rigorous, consistent AI outputs

Structured prompts ensure every analysis follows the same framework, making results comparable and actionable across different AI platforms.

Safety and compliance built in

Built-in guardrails prevent alcohol-related content violations, protecting your brand from regulatory risks and reputation damage.

Actionable insights you can trust

Scoring rubrics and data capture schemas transform AI outputs into structured data you can analyze, track, and act upon.

Quickstart guide

Before diving into the detailed prompts, here's how to get started quickly:

  1. Choose your workflow: Baseline Assessment, Content Optimization, or Customer Insight Mining
  2. Select your analysis scope: Single winery or multi-brand competitive set
  3. Copy-paste the prompt variant into your preferred AI platform (ChatGPT, Perplexity, Google AI)
  4. Review AI output using the provided scoring rubric and evaluator instructions
  5. Capture results in the markdown or CSV format for downstream analysis
  6. Apply safety and compliance checks for alcohol-related content
  7. Schedule weekly sampling and KPI tracking as per the sampling plan

Implementation checklist

Use this checklist to implement the prompt kit:

1

Define target winery or brand set

Identify which winery or competitive set you want to analyze. Gather all relevant information including product lists, regions, and key brand attributes.

2

Select workflow and prompt variant

Choose the appropriate workflow (Baseline Assessment, Content Optimization, or Customer Insight Mining) and select single winery or multi-brand variant based on your needs.

3

Copy-paste prompt into AI platform

Use the exact prompt text provided, filling in the placeholder variables with your specific brand information. Test on ChatGPT, Google AI, or Perplexity.

4

Use chain-of-thought alternatives if needed

For complex analyses, use the chain-of-thought prompt variants that encourage step-by-step reasoning before final output.

5

Apply scoring rubric and evaluator instructions

Systematically evaluate AI outputs using the provided rubrics. Check for accuracy, policy consistency, and transaction readiness.

6

Record outputs in data capture schema

Store results in the provided markdown or CSV format for consistent tracking and analysis over time.

7

Verify compliance with safety guardrails

Ensure all outputs pass safety checks for age restrictions, shipping compliance, and responsible drinking messaging.

8

Run negative controls and adversarial tests

Test with incomplete or conflicting data to verify the AI's resistance to hallucinations and ability to handle edge cases.

9

Schedule weekly sampling and KPI review

Establish a regular cadence for testing and tracking key performance indicators to monitor AI performance over time.

10

Iterate and optimize content based on insights

Use the insights gathered to improve your brand's product information, policies, and content strategy.

Workflow A: Baseline assessment

The Baseline Assessment workflow evaluates your current brand positioning, messaging accuracy, and compliance. Use this to understand where your brand stands today before making improvements.

Single winery prompt

Use this prompt when analyzing a single winery's brand positioning and compliance:

1

Prompt template

Use this prompt template:

Code
You are an expert wine brand analyst. Assess the following winery's brand positioning, messaging accuracy, and compliance with alcohol advertising policies. Provide a structured markdown output including: brand strengths, weaknesses, policy risks, and transaction readiness indicators.

Winery Name: **{winery_name}**
Region: **{region}**
Key Products: **{products_list}**

Safety: Ensure no promotion to underage audiences or illegal shipping claims.

Return only the final markdown.
2

What to replace

Replace {winery_name} with your winery's name, {region} with the wine region (e.g., Napa Valley, Willamette Valley), and {products_list} with a comma-separated list of key products or wine names.

3

Expected output

A markdown formatted output containing brand strengths, weaknesses, policy risks, and transaction readiness scores. Use the scoring rubric to evaluate the quality and accuracy of the response.

Multi-brand competitive set prompt

Use this prompt when comparing multiple wine brands in a competitive analysis:

1

Prompt template

Use this prompt template:

Code
You are an expert wine brand analyst. Compare the following wine brands on positioning, messaging accuracy, policy consistency, and transaction readiness. Provide a markdown formatted list with each brand's profile including strengths, weaknesses, compliance risks, and readiness score.

Brands: **{brand_list}**

Safety: Avoid any alcohol promotion to minors or unlicensed shipping claims.

Return only the final markdown.
2

What to replace

Replace {brand_list} with a structured list of brands, each including name, region, and key products. Format as a clear list or structured data.

3

Expected output

A markdown formatted list where each item represents one brand's analysis. This enables side-by-side comparison of competitive positioning and compliance.

Workflow B: Content optimization

The Content Optimization workflow helps improve your marketing copy and product descriptions for clarity, compliance, and engagement. Use this to refine how your brand communicates with customers.

Single winery content optimization

Optimize product descriptions and marketing copy for a single winery:

1

Prompt template

Use this prompt template:

Code
You are a content optimization specialist for wine brands. Rewrite the following product descriptions to maximize clarity, engagement, and compliance with alcohol advertising policies. Return a markdown formatted output with original text, optimized text, and compliance notes.

Product Descriptions: **{descriptions}**

Safety: Ensure no underage appeal or false shipping info.

Return only the final markdown.
2

What to replace

Replace {descriptions} with your current product descriptions, tasting notes, or marketing copy that you want to optimize.

3

Expected output

A markdown formatted output with original text, optimized versions, and specific compliance notes explaining any changes made for regulatory alignment.

Multi-brand content optimization

Compare and optimize content across multiple brands:

1

Prompt template

Use this prompt template:

Code
You are a content optimization specialist. Analyze and optimize marketing copy for the following wine brands. Return a markdown formatted list with original and optimized texts plus compliance and engagement scores.

Brands & Descriptions: **{brand_descriptions}**

Safety: Avoid any policy violations related to alcohol promotion.

Return only the final markdown.
2

What to replace

Replace {brand_descriptions} with structured data containing each brand's name and their current product descriptions or marketing copy.

3

Expected output

A markdown formatted list with optimized content for each brand, including compliance scores and engagement metrics to help prioritize improvements.

Workflow C: Customer insight mining

The Customer Insight Mining workflow extracts actionable insights from customer reviews and social media about wine brands. Use this to understand customer sentiment, identify product feedback, and spot compliance issues.

Single winery customer insights

Analyze customer feedback for a single winery:

1

Prompt template

Use this prompt template:

Code
You are a customer insight analyst. Analyze the following customer reviews for **{winery_name}** to identify key sentiment themes, product feedback, and compliance flags. Return a markdown formatted output with sentiment scores, themes, and any policy risks.

Reviews: **{reviews}**

Safety: Flag any content that promotes unsafe alcohol use or illegal sales.

Return only the final markdown.
2

What to replace

Replace {winery_name} with your winery's name and {reviews} with customer reviews, social media mentions, or feedback you want to analyze.

3

Expected output

A markdown formatted output with sentiment analysis, key themes, product feedback patterns, and any compliance concerns identified in customer communications.

Multi-brand customer insights

Compare customer feedback across multiple brands:

1

Prompt template

Use this prompt template:

Code
You are a customer insight analyst. Analyze customer feedback across these wine brands to identify comparative sentiment trends, product strengths, weaknesses, and compliance issues. Return a markdown formatted list with detailed insights per brand.

Brands & Reviews: **{brand_reviews}**

Safety: Highlight any content violating alcohol advertising policies.

Return only the final markdown.
2

What to replace

Replace {brand_reviews} with structured data containing each brand's name and associated customer reviews or social media mentions.

3

Expected output

A markdown formatted list with comparative insights showing how each brand performs in customer sentiment, product satisfaction, and compliance adherence.

Scoring rubrics and data capture

To ensure consistent evaluation of AI outputs, use these scoring rubrics and data capture schemas. They transform subjective assessments into measurable, trackable metrics.

Scoring rubric for baseline assessment

1

Answer accuracy (0-5)

Measures correctness and relevance of brand information. Score 5 if all facts are verifiable and accurate, 0 if information is incorrect or fabricated.

2

Policy consistency (0-5)

Evaluates adherence to alcohol advertising policies. Score 5 if all policy statements align with regulations, 0 if violations are present.

3

Transaction readiness (0-5)

Assesses completeness for enabling purchase decisions. Score 5 if all necessary information for purchase is present, 0 if critical details are missing.

Data capture schema

Use this markdown format to consistently capture and store analysis results:

markdown
## Brand Analysis: **{brand_name}**

**Date:** **{ISO8601 datetime}**

### Strengths
- **{strength 1}**
- **{strength 2}**
- **{strength 3}**

### Weaknesses
- **{weakness 1}**
- **{weakness 2}**
- **{weakness 3}**

### Policy Risks
- **{risk 1}**
- **{risk 2}**
- **{risk 3}**

### Transaction Readiness Score
**{score}**/5

For CSV export, use these headers:

csv
brand_name,strengths,weaknesses,policy_risks,transaction_readiness_score,timestamp

Safety and compliance guardrails

These guardrails protect your brand from regulatory violations and reputation damage. Always verify AI outputs pass these checks:

  • Age restriction: No content should target or appeal to underage audiences. Verify language doesn't encourage underage consumption.
  • Shipping compliance: Avoid claims about shipping alcohol to prohibited regions. Verify all shipping statements match your actual capabilities.
  • Responsible drinking: No encouragement of excessive or unsafe alcohol consumption. Check for language promoting moderation.
  • Policy adherence: Align with major alcohol advertising regulations including TTB, FDA, and local laws. Verify all policy statements are accurate and current.

Evaluator instructions to reduce hallucinations

AI assistants can sometimes generate plausible-sounding but incorrect information. These instructions help evaluators identify and penalize hallucinations:

  • Verify factual claims: Cross-check all brand information against known winery data or official sources. Don't accept unverified claims.
  • Cross-check policies: Validate policy-related statements against your actual regulatory guidelines and internal policies.
  • Use scoring rubric consistently: Apply the rubric systematically. Penalize unsupported or fabricated information with lower scores.
  • Prefer structured outputs: Favor clear, structured markdown over free text. Structured outputs are easier to validate and less prone to hallucination.
  • Use chain-of-thought privately: While chain-of-thought prompts can improve reasoning, only evaluate the final markdown outputs, not the reasoning process.

Chain-of-thought alternatives

For complex analyses, use chain-of-thought prompts that encourage step-by-step reasoning before final output. This helps the AI think through the problem more thoroughly while keeping outputs clean.

Example chain-of-thought prompt:

Think step-by-step privately about the winery's brand strengths, weaknesses, and compliance risks. Then return only the final markdown output without revealing your reasoning.

This approach encourages thorough internal reasoning while preventing extraneous explanations that can make evaluation more difficult.

Negative controls and adversarial testing

To verify your prompts resist hallucinations and handle edge cases, test with negative controls and adversarial examples:

  • Negative control prompt: Provide incomplete or misleading winery data using a real brand name to test hallucination resistance. Example:
Code
Analyze the brand data:
Winery Name: "Domaine Chandon"
Products: "N/A"
Region: ""

Return markdown with brand analysis or state 'insufficient data'.
  • Adversarial example: Include conflicting product information or ambiguous policy statements to test AI robustness. This helps identify where the AI might make incorrect assumptions or generate fabricated details.

These tests help ensure your prompts produce reliable outputs even when input data is incomplete or contradictory.

Sampling plans and KPI definitions

Establish a regular sampling cadence and track key performance indicators to monitor AI performance over time:

Sampling cadence: Run prompts weekly on a random sample of 10-20 brands or products. This provides consistent monitoring without overwhelming your team.

Key performance indicators:

  • Answer Accuracy Rate: Percentage of outputs scoring 4 or higher on accuracy (target: 90%+)
  • Policy Violation Rate: Percentage of outputs flagged for policy inconsistencies (target: <5%)
  • Transaction Readiness Index: Average readiness score across samples (target: 4.0+)
  • Hallucination Rate: Percentage of outputs with fabricated or unverifiable information (target: <5%)

Track these KPIs weekly to monitor AI performance and compliance adherence. Use trends to identify when prompts need refinement or when brand information needs updates.

Consistency with eLLMo's brand voice and differentiators

When using these prompts, maintain consistency with eLLMo AI's approach to responsible AI in regulated industries:

  • Clear, professional, data-driven language: Avoid jargon and focus on actionable insights
  • Emphasize transparency and compliance: Highlight how the framework ensures regulatory alignment
  • Support decision-making: Provide insights that help wineries make informed choices about their brand positioning
  • Responsible AI commitment: Demonstrate how the framework protects brands from compliance risks while enabling growth

Putting it all together

This prompt kit empowers wine industry analysts and marketers to harness AI effectively and responsibly. By following the structured workflows, safety guardrails, and evaluation protocols aligned with eLLMo AI's framework, teams can confidently generate accurate, compliant, and transaction-ready insights that drive brand success.

Whether analyzing a single winery or a competitive multi-brand set, these prompts ensure rigorous, consistent, and safe AI outputs tailored to the wine industry's unique regulatory environment and business needs.

Get Started with eLLMo AI

Ready to ensure your winery is accurately represented across AI platforms? Schedule a demo to see how eLLMo AI automates brand analysis, policy compliance, and transaction readiness without manual prompt management.

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A rigorous prompt kit for wine brand analysis | eLLMo AI Blog