🍳 Food Prompt
How E-commerce Food Critics Can Use Claude to Fix Poor Online Reviews in Developing a Restaurant Concept
From poor online reviews to improved average spend — Intermediate techniques for E-commerce food professionals developing a restaurant concept
The Prompt
You are a senior restaurant brand consultant and reputation management specialist with 11 years of experience writing negative review response strategies, restaurant concept development frameworks, and brand positioning documents for food businesses where a cluster of poor online reviews is signaling a concept gap between what the restaurant believes it is offering and what customers are actually experiencing — and where the review response strategy must simultaneously protect the brand reputation and inform the concept refinement that prevents the same review from appearing again next month. Help me write a restaurant response to a negative review so I can improve average spend per customer and build a response framework that converts a negative review into a concept improvement signal rather than a defensive PR exercise.
My situation:
- Restaurant concept and target positioning: [e.g., "a modern Italian trattoria aiming for a neighborhood fine casual positioning at a $55 to $75 per person average spend — the concept is a 60-cover restaurant that opened 4 months ago and is developing its identity"]
- Current negative review pattern: [e.g., "a cluster of 11 reviews in the past 6 weeks averaging 2.8 stars — 7 of the 11 mention the same three issues: portions feeling small for the price, service feeling rushed, and the menu being confusing between casual and fine dining in its ambiguity"]
- Average spend problem: [e.g., "current average spend is $48 per person versus the $55 to $75 target — customers are not ordering the premium dishes and the beverages that produce the target spend, and the review pattern suggests the value perception is blocking the full menu exploration"]
- Restaurant concept development stage: [e.g., "the concept is in active development — the menu, the service style, and the interior design are all subject to refinement based on the first 4 months of trading data, and the reviews are being used as a product development input"]
- Review platform and public visibility: [e.g., "Google Reviews (32 reviews total, 3.6 average) and TripAdvisor (18 reviews, 3.4 average) — both platforms rank prominently in the restaurant's local search results"]
- Review response voice constraint: [e.g., "the owner is the reviewer and the brand voice must be personal and considered rather than corporate — responses should feel written by someone who cares about the feedback, not by a reputation management department"]
- Concept improvement goal: [e.g., "want the review response strategy to serve as a public demonstration of the concept's values while the refinement is underway — each response should signal to a potential new customer that the team is listening and improving"]
Deliver:
1. A negative review response template for the three recurring issues — a response for the portion size complaint (acknowledging the feedback, explaining the sharing concept or the kitchen's philosophy without being defensive, and inviting the reviewer to return for a specific experience that recontextualizes the portion sizes), a response for the rushed service complaint (acknowledging the specific failure, explaining the intended pace without excusing the execution gap, and offering a direct resolution), and a response for the concept ambiguity complaint (using the response to clarify the trattoria positioning for the reviewer and future readers simultaneously)
2. A review pattern analysis brief — a structured process for analyzing the 32 Google reviews and 18 TripAdvisor reviews to identify the three most frequent complaints, the two most frequently praised elements, the specific service moments that appear most often in negative reviews, and the menu items most frequently mentioned in both positive and negative reviews
3. A concept refinement signal brief — a framework for using the review pattern analysis as a concept development input, covering the three specific menu or service changes the current review pattern suggests should be prioritized in the next 60 days, each with the expected impact on the average spend if the change is implemented
4. A premium dish and beverage upsell brief — the specific service language and menu design changes that increase the likelihood of a customer ordering the premium dishes and beverages that produce the $55 to $75 average spend target, derived from the review analysis showing why customers are defaulting to the lower-spend options
5. A proactive review request strategy — the specific moment in the dining experience (immediately after the dessert course is cleared, before the bill is presented) and the staff script for requesting a review from tables who have verbally expressed satisfaction, with the platform recommendation based on which platform has the most impact on the restaurant's local search visibility
6. A concept narrative document — a 200-word internal brief describing the trattoria positioning that every staff member reads during onboarding, covering the intended price-to-value proposition, the sharing philosophy for portions, the pacing intention for service, and the balance between casual warmth and fine dining quality that defines the concept, reducing the execution gap between the concept intention and the customer experience
7. A review response approval process — the two-step process for reviewing draft responses before publishing (the owner reads for personal voice authenticity, the restaurant manager reads for factual accuracy and policy compliance), with the maximum response time target for negative reviews (48 hours from posting) and the escalation process for reviews containing specific allegations
8. A 90-day reputation recovery measurement brief — four metrics tracked monthly (average review score on Google and TripAdvisor, review response rate, new review volume, and average spend per cover), with the threshold at each metric that confirms the response strategy and concept refinements are producing the intended reputation and spend improvement before the 90-day window closes
**Write every review response template and concept refinement component assuming the restaurant owner is emotionally invested in the concept and occasionally defensive when reading negative feedback — every response template must be easy to personalize without requiring the owner to rewrite the defensive instinct out of their first draft, and every concept refinement signal must be framed as an opportunity rather than a failure so the feedback is actionable rather than demoralizing.**
💡 How to use this prompt
- Complete the review pattern analysis from output item 2 before writing a single review response. The three recurring complaints in the current review cluster are the same signal — and responding to each review as if it is an isolated event misses the pattern that is telling the concept where the execution is falling short. The pattern analysis reveals whether the same kitchen, service, or concept gap is generating all three complaint types, which determines whether the response strategy needs a single concept clarification or three separate corrections.
- The most common mistake is writing review responses that close the conversation rather than inviting it forward. A response that says "we're sorry you felt that way and we hope you'll give us another chance" is a customer service close — a response that says "we'd love to walk you through our sharing philosophy on a return visit, and we've reserved a specific table for you to try our seasonal tasting format" is a concept re-engagement offer. Review responses for a restaurant in active concept development must invite the reviewer into the improvement rather than apologizing and ending the conversation.
- Claude outperforms ChatGPT on this task because it follows multi-step instructions more precisely and maintains consistent tone across long outputs. Use Claude for the full draft, then paste into ChatGPT if you need a faster, shorter variation.
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About This Food AI Prompt
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