AI TripAdvisor Reviews Analyzer

What is TripAdvisor Reviews Scraper with AI Insights?

TripAdvisor Reviews Scraper with AI Insights extracts public reviews from any TripAdvisor hotel, restaurant, or attraction page — without a browser. Paste one or more URLs, click Start, and get a structured dataset of reviews plus an optional AI-powered analysis of guest sentiment, top themes, and common complaints. No TripAdvisor account required.

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Why no browser?

	This Actor	Browser-based
Startup	Seconds	Minutes
Memory	~100 MB	~1 GB
Proxy	Auto-fallback only	Always needed

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What can this Actor do?

• ⚡ 10× faster startup — no browser, no 1 GB image to pull
• 🌐 Scrape multiple places in one run
• ⭐ Filter by star rating, date range, and language
• 🤖 AI analysis — sentiment, top themes, complaints, and narrative summary per place
• 📋 One structured row per review — export as JSON, CSV, Excel, or HTML
• 🗃️ Place summaries in Places.json and Places.md (including AI insights)
• 🔄 Automatic proxy fallback — no proxy configuration needed
• ☁️ Full Apify platform support: scheduling, webhooks, API, integrations

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What data can you extract from TripAdvisor?

Data point	Description
Review title	Short headline written by the reviewer
Review text	Full body of the public review
Star rating	1–5 overall rating
Published date	When the review was posted (YYYY-MM-DD)
Travel date	Month/year of the stay or visit
Trip type	Family, Business, Couples, Solo, etc.
Reviewer name	Public display name
Helpful votes	How many users found the review helpful
Owner response	Management reply when present
Sub-ratings	Cleanliness, service, etc. when available

Place-level data (overall rating, rating distribution, total review count) is in Places.json.

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AI-powered Analysis

Enable AI Analysis to get insights based on up to 1,000 reviews per place. Results are embedded directly into Places.json and Places.md — no separate files.

AI output	Description
Overall Sentiment	Positive / Neutral / Negative split with a dominant label
Top Positive Themes	3–5 recurring strengths guests mention most
Top Negative Themes	3–5 recurring pain points
Common Complaints	Up to 5 specific, actionable complaints
Summary	3–5 sentence narrative of the overall guest experience

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How to scrape TripAdvisor reviews — step by step

1. Open this Actor in Apify Console and go to the Input tab.
2. Paste one or more TripAdvisor place URLs (hotel, restaurant, or attraction).
3. Optionally set Max reviews, date range, ratings, and language filters.
4. To add AI insights, toggle AI Analysis on.
5. Click Start — proxy is handled automatically.
6. When done, open the Dataset tab for reviews, or Storage → Key-value store for Places.json and Places.md.

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How much does it cost?

Scraping reviews costs $1 per 1,000 reviews. Runs are fast. AI analysis is additional and billed by your AI provider based on the number of reviews analysed.

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Input

Field	Type	Description
Place URLs (startUrls)	URL list	Required. TripAdvisor hotel, restaurant, or attraction pages.
Max reviews per place (maxReviewsPerPlace)	Integer	Cap per place. 0 = no limit.
Start date (startDate)	YYYY-MM-DD	Only reviews on or after this date.
End date (endDate)	YYYY-MM-DD	Only reviews on or before this date.
Review ratings (reviewRatings)	Multi-select	Filter by star rating. Leave empty for all.
Review language (language)	Select	Filter by language. Leave empty for all.
AI Analysis (aiSummary)	Boolean	Enable AI sentiment analysis. Default: false.

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Output

Dataset — one row per review

{
  "id": "942837461",
  "placeName": "The Waterfront Hotel",
  "title": "Wonderful location and friendly staff",
  "text": "We stayed for 4 nights in March. The location right on the seafront...",
  "rating": 5,
  "publishedDate": "2025-03-10",
  "travelDate": "2025-03",
  "tripType": "Couples",
  "lang": "en",
  "reviewerName": "Traveler_Malta2025",
  "helpfulVotes": 2
}

Places.json — place metadata with embedded AI insights

[
  {
    "id": "264939",
    "name": "The Waterfront Hotel",
    "placeType": "hotel",
    "rating": "4.4",
    "totalReviews": 3930,
    "scrapedReviews": 300,
    "city": "Sliema",
    "country": "Malta",
    "ratingDistribution": { "excellent": 2427, "good": 982, "average": 360, "poor": 103, "terrible": 58 },
    "aiSummary": {
      "overallSentiment": { "positive": 89.3, "neutral": 7.0, "negative": 3.7, "label": "positive" },
      "topPositiveThemes": [
        { "theme": "Seafront location", "description": "Guests consistently praise the prime waterfront position." },
        { "theme": "Friendly staff", "description": "Staff warmth and helpfulness are highlighted across reviews." },
        { "theme": "Breakfast quality", "description": "The buffet receives high marks for variety and freshness." }
      ],
      "topNegativeThemes": [
        { "theme": "Noise levels", "description": "Street noise is mentioned by guests in promenade-facing rooms." },
        { "theme": "Parking", "description": "No on-site parking; nearby options are limited." }
      ],
      "commonComplaints": ["Street noise at night", "No on-site parking", "Wi-Fi drops in some rooms"],
      "summary": "The Waterfront Hotel is overwhelmingly well-received, with strong praise for its seafront location and warm staff. The breakfast and room cleanliness stand out as consistent strengths. Street noise and parking are the most common friction points. Overall, the hotel delivers a high-quality experience for the majority of guests.",
      "reviewsAnalyzed": 300,
      "generatedAt": "2026-04-16T09:15:00Z"
    }
  }
]

Places.md — human-readable summary (excerpt)

## 1. The Waterfront Hotel

- **Rating**: 4.4 / 5  |  **Total reviews**: 3,930  |  **Scraped**: 300
- **Location**: Sliema, Malta

### AI Analysis

- **Overall Sentiment**: Positive - Positive 89.3% / Neutral 7.0% / Negative 3.7%
- **Top positive themes**: Seafront location, Friendly staff, Breakfast quality
- **Top negative themes**: Noise levels, Parking
- **Common complaints**: Street noise at night, No on-site parking, Wi-Fi drops in some rooms
- **Summary**: The Waterfront Hotel is overwhelmingly well-received...

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How it works

1. Cookie seeding — one GET request per place using Chrome TLS impersonation (curl_cffi) to collect DataDome session cookies. No HTML is scraped.
2. Place metadata — from TripAdvisor's GraphQL API or optionally via the official Content API.
3. Review pagination — 50 parallel GraphQL requests per wave (500 reviews/wave).
4. Automatic proxy escalation — starts without proxy; retries with Apify Residential Proxy on block; reuses the same IP for all places once one succeeds.
5. AI analysis — up to 1,000 reviews per place analysed in batches, then aggregated into the final aiSummary.

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Tips

• 🧪 Test small first — one URL, Max reviews = 20, before a large run.
• 📅 Incremental pulls — set startDate to yesterday on a schedule to collect only new reviews.
• 🔗 Automate — use Apify Schedules and webhooks or connect to Make, Zapier, n8n, and Google Sheets via integrations.

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FAQ and support

Is it legal to scrape TripAdvisor?

This Actor collects only public content visible to any visitor — review text, ratings, dates, and display names. It does not access private accounts or hidden data. You are responsible for complying with TripAdvisor's Terms of Use and applicable data-protection regulations (e.g. GDPR). See also: Is web scraping legal? — Apify blog.

Does TripAdvisor have an official API?

TripAdvisor's Content API covers location details (free tier: 5,000 calls/month) but not review data at scale. This Actor uses TripAdvisor's internal GraphQL endpoint for reviews.

Where can I get help?

• 💬 Apify Discord
• 🐛 Issues tab on this Actor page
• 📖 Apify documentation