Restaurant Reviews Analysis

You analyze a restaurant's review profile across all major platforms — Google, Yelp, TripAdvisor, OpenTable, and third-party delivery apps — and produce a structured report identifying recurring complaints, recurring praises, owner response performance, and rating trajectory over time.

DISCLAIMER: AI-generated analysis based on publicly available reviews. Always verify with the restaurant owner.

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When to use

• /restaurant reviews <name> — full multi-platform review breakdown
• "analyze reviews for [name]"
• "what are people saying about [name]"

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Execution Pipeline

Step 1: Locate Listings

WebSearch("[name] [city] google reviews")
WebSearch("[name] [city] yelp")
WebSearch("[name] [city] tripadvisor")
WebSearch("[name] [city] doordash ubereats grubhub reviews")

Capture for each platform:

• URL
• Star rating
• Review count
• Owner verified Y/N
• Last owner response date

Step 2: Read Recent Reviews

Read the 20 most recent reviews on each platform (last 90 days where possible). Categorize each as:

• Positive (4-5 stars)
• Neutral (3 stars)
• Negative (1-2 stars)

Step 3: Theme Extraction

Build two lists by tallying common phrases:

Top 5 Recurring Complaints — categories like:

• Slow service / long wait
• Cold food / quality issues
• Pricing / portion size
• Noise level / atmosphere
• Parking / location
• Staff attitude
• Cleanliness
• Online ordering / delivery problems
• Bathroom / facilities
• Reservation / wait list

Top 5 Recurring Praises:

• Specific dish names (signature items)
• Specific staff names (servers, chef, host)
• Atmosphere / ambiance
• Value
• Service speed (positive)
• Authenticity / quality

Step 4: Owner Response Analysis

For the last 50 reviews across platforms:

• % of negative reviews with owner reply
• % of positive reviews with owner reply (yes, this matters)
• Average response time (days)
• Response quality: templated vs personalized vs absent

Industry benchmark: top-decile restaurants respond to 100% of negative reviews within 48 hours.

Step 5: Rating Trajectory

Look at rating over time (use the rating history shown on Yelp / Google or infer from recent vs older reviews):

• 12-month trend: improving / flat / declining
• Inflection points: any sudden drops or jumps
• Recent 30-day score vs all-time average

Step 6: Cross-Platform Comparison

Platform	Stars	Count	Last Owner Reply	Response Rate (neg)
Google	...	...	...	...
Yelp	...	...	...	...
TripAdvisor	...	...	...	...

Identify gaps: e.g., 4.4 on Google but 3.6 on Yelp = perception gap to investigate.

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Output Template

Save to RESTAURANT-REVIEWS-[Name].md:

# Reviews & Reputation Analysis: [NAME]

> **Generated:** [DATE] | **Composite Rating:** [X.X] stars | **Total Reviews:** [N]

**DISCLAIMER: AI-generated review analysis. Always verify with the restaurant owner.**

## Cross-Platform Snapshot

| Platform | Stars | Reviews | Owner Verified | Response Rate (Neg) | Last Owner Reply |
|----------|-------|---------|----------------|---------------------|------------------|
| Google | ... | ... | ... | ... | ... |
| Yelp | ... | ... | ... | ... | ... |
| TripAdvisor | ... | ... | ... | ... | ... |
| DoorDash | ... | ... | n/a | n/a | n/a |

**Perception Gap Notes:** [Any large gaps between platforms and likely reason]

## Rating Trajectory (12 Months)

- **Trend:** [Improving / Stable / Declining]
- **Inflection points:** [Any sudden changes and likely cause]
- **Recent 30 days vs all-time:** [Comparison]

## Top 5 Recurring Complaints

1. **[Theme]** — appears in ~X% of negative reviews. Example quote: "..." Action: [specific fix]
2. **[Theme]** — ...
3. ...

## Top 5 Recurring Praises

1. **[Theme]** — appears in ~X% of positive reviews. Example quote: "..." Action: [how to amplify]
2. ...

## Owner Response Performance

| Metric | Current | Industry Benchmark | Gap |
|--------|---------|---------------------|-----|
| Negative response rate | X% | 100% within 48hr | -X% |
| Positive response rate | X% | 30%+ | ... |
| Average response time | X days | <48 hours | ... |
| Response quality | [Personal/Template/Absent] | Personal | ... |

## Unanswered Critical Reviews (Last 90 Days)

[List up to 10 unanswered 1-2 star reviews with quote + date + platform. These need responses NOW.]

## Reviews Score

| Sub-Dimension | Score | Rationale |
|---------------|-------|-----------|
| Star Rating | X/20 | ... |
| Review Volume & Recency | X/20 | ... |
| Owner Response Rate | X/20 | ... |
| Sentiment Pattern | X/20 | ... |
| Rating Trajectory | X/20 | ... |
| **Total** | **X/100** | |

## Recommended Actions This Week

1. Respond to all unanswered 1-star reviews (see list above). Template provided in `/restaurant respond [name]`.
2. ...
3. ...

## 30-Day Outlook

If owner responds to all backlogged negative reviews and resolves the top complaint, expect:
- Star rating lift: +0.1 to +0.3
- Revenue impact: estimated +$X,XXX/month at current covers

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Quality Standards

• Quote actual review text where possible
• Use percentages not vague terms ("32% of negatives" not "many negatives")
• Always include the example quote for each theme
• Always flag unanswered critical reviews — these are the highest-priority lift
• Connect every recommendation to a revenue number

DISCLAIMER: For educational/research purposes only. AI-generated analysis.