TripAdvisor Reviews Scraper & AI Review Analysis: From Hotel URL to Action Plan

Guests tell you exactly what to fix, but it is buried in hundreds of TripAdvisor reviews. A manager rarely has the hours to read them all, and a star average does not say whether the problem is housekeeping, noise, breakfast or the front desk.

Paste a TripAdvisor hotel, restaurant or attraction URL. The Actor collects the reviews for you and turns them into a manager-ready action plan: sentiment, rating distribution, recurring themes (cleanliness, staff, food, location, noise, value), top complaints and praises, prioritized fixes with benefit and cost, quick wins, and the single most important step for this week.

• One input: a TripAdvisor page URL. Or paste your own reviews from any source.
• Collection included: reviews are gathered through proven TripAdvisor review scrapers from Apify Store, with automatic fallback if one fails.
• Decisions, not just scores: every finding is tied to an action with priority, risk, benefit and cost.
• Five output languages: English, Turkish, German, Spanish, French.
• Safe to try: if no reviews are found, you are not charged for analysis.
• Weekly monitoring: turn on onlyNewReviews and schedule it; each run analyzes and charges only reviews posted since the last run. No new reviews means only the start fee.

What it costs: about $0.70 for 100 reviews from a TripAdvisor URL ($0.65 analysis and report, about $0.05 collection). Details in Pricing.

---

At a glance

Input	TripAdvisor page URL (startUrl) or your own review list (reviews)
Works for	Hotels, B&Bs, resorts, restaurants, cafés, attractions and tours
Output	Prioritized action table (dataset) + full manager report (key-value store MANAGER_REPORT)
Analysis	Sentiment, star distribution, recurring themes, top complaints and praises, action plan, quick wins, critical step, competitor opportunities, executive summary
Reviews per run	10-500 from a URL; any number when you paste your own
Pricing	Pay per 100 reviews analyzed + per report; see Pricing
Runs on	Apify Console, API, schedules, n8n, Make, Zapier, AI agents via MCP

---

Quick start

1. Paste a TripAdvisor page URL into TripAdvisor page URL, for example a hotel's Hotel_Review-...html page.
2. Set Max reviews to collect (100 is a good default) and the output language.
3. Click Start. Open the Dataset tab for the action table and the key-value store for MANAGER_REPORT.

What the action table looks like

Priority	Issue / Area	Risk of Inaction	Risk Level	Benefit	Cost	Score	Recommended Action
1	Street noise in front-facing rooms	Sleep complaints keep pulling the rating down	High	High	Medium	8.7	Fit acoustic seals on front windows; offer quiet-side rooms at booking
2	Slow check-in at peak hours	First impression suffers in many reviews	Medium	High	Low	8.2	Add a second desk 14:00-17:00; pre-send check-in forms by email
3	Breakfast variety	Repeat guests mention the same menu	Low	Medium	Low	6.1	Rotate two hot items weekly; add a local specialty

Illustrative example; your run reports its own findings, based only on the reviews it collected. Scores are relative within your run, so compare actions to each other rather than across properties.

---

Why hospitality managers use it

Most review dashboards stop at an average score and a word cloud. That does not tell a general manager whether to retrain the front desk, fix the windows, or change the breakfast supplier. This Actor works like an analyst who makes recommendations:

1. It reads every review in small chunks, so nothing is skipped. If a model response is ever truncated, the chunk is split and analyzed again instead of being silently dropped.
2. It groups problems into themes and counts them, so you see how widespread each issue is.
3. It turns each theme into an action with the risk of doing nothing, a benefit and cost estimate and a score to sort by.
4. It separates quick wins you can do this week from investments that need a budget.
5. It names one critical step, so the report ends in a decision.

Rating dashboard vs. this Actor

	Typical rating dashboard	This Actor
Collects the reviews	Needs a subscription or connection	Yes, from a public TripAdvisor URL
Output	Scores, charts, word clouds	Themes, complaints, praises, prioritized actions
Tells you what to do	No	Yes: action, risk, benefit, cost, score
Works on competitors	Usually not	Any public TripAdvisor page
Ready for the owner	Needs interpretation	Executive summary and one critical step

---

Who it is for

• Hotel general managers and owners who need priorities, not more charts.
• Restaurant owners and F&B managers tracking service, food and value feedback.
• Hospitality groups comparing properties on the same basis.
• Revenue and marketing teams looking for strengths to promote.
• Consultants and agencies delivering review audits to hospitality clients.
• Tour and attraction operators improving guest experience.

---

What you get

Dataset: the action table

One row per prioritized action, sorted by score: Priority, Issue / Area, Risk of Inaction, Risk Level, Benefit, Cost, Benefit/Cost, Score, Recommended Action. The number of rows is set by Actions shown in the table (default 5); the full list is in the report.

Key-value store: MANAGER_REPORT

Key	Content
overall_sentiment	Overall tone of the reviews
rating_distribution	Count of 1-5 bubble ratings
review_count	Number of reviews analyzed
themes	Recurring themes with frequency and positive/negative direction
top_complaints / top_praises	The most frequent negatives and positives
competitor_opportunities	What guests miss here that a competitor could offer, or you could offer against competitors
quick_wins	Low-effort, high-impact moves
critical_step	The single most important action this week
executive_summary	A short paragraph for an owner, board or client
all_actions	The full prioritized action list

---

Worked example: a city hotel with a slipping rating

A 90-room city hotel dropped from 4.5 to 4.2 bubbles over a season.

1. Run on the hotel's page with 200 reviews. The table puts "street noise" and "slow check-in" at the top.
2. Check themes: noise appears mostly in 2-3 bubble reviews from front-facing rooms; check-in delays appear in many reviews but rarely as the main complaint. Noise drives the rating; check-in drives the first impression.
3. Do the quick_wins: allocate quiet rooms to light sleepers at booking, add a peak-hour desk, reply to recent noise reviews with what is being done.
4. Plan the critical_step: get quotes for window seals on the front side.
5. Run on three nearby competitors. If they share the noise issue, "quiet rooms guaranteed" becomes a selling point once fixed.
6. Re-run after the season to confirm the noise theme is shrinking.

---

What to do with each part of the report

Report part	Typical owner	Typical use
critical_step	GM or owner	This week's decision
quick_wins	Department heads	Staffing, room allocation, menu tweaks, signage
all_actions	Management and maintenance	Budget planning and capex priorities
top_complaints	Front office and guest relations	Reply templates, staff briefings
top_praises	Marketing	Website copy, OTA descriptions, ad angles in guests' words
competitor_opportunities	Sales and revenue	Positioning against the competitive set
executive_summary	Owners, investors, clients	One paragraph for a monthly report

---

Use cases

Hotels and resorts

Monthly review audits per property, briefing notes for department heads, and evidence for capex requests ("noise appears in X% of negative reviews").

Restaurants and cafés

Separate food, service, wait time and value issues. Use praises to decide which dishes to feature and complaints to decide what to change on the menu.

Hospitality groups

Run the same settings across properties to compare themes. Shared complaints point to group-level processes; unique ones to local management.

Competitive benchmarking

Analyze your competitive set. Their top complaints are your marketing angles; their top praises are the bar you need to meet.

Consultants and agencies

Deliver a professional review audit on day one of an engagement. The action table and summary go straight into a client report.

Tourism boards and destination marketers

Analyze popular attractions to understand what visitors love and what frustrates them.

Property investors and asset managers

Before acquiring or refinancing a hotel, analyze its recent reviews. Recurring maintenance or service themes are an early indicator of hidden capex and operational issues that a financial report will not show.

Tour operators and travel agencies

Check the hotels and restaurants in your packages before the season. Replace or brief partners whose recurring complaints could reach your own customer reviews.

---

How it works

1. Collect. For a TripAdvisor URL, the Actor calls an ordered chain of TripAdvisor review scrapers from Apify Store (cheapest first), each with a spending cap. If one fails or returns less than half of what you asked for, the next is tried, and the best result is kept.
2. Normalize. Review text, title and rating are put into one format.
3. Analyze in chunks. Ten reviews at a time go to a language model with a strict JSON format.
4. Merge chunk results into themes, complaints, praises and actions with counts.
5. Prioritize actions by risk, benefit and cost.
6. Report: the action table goes to the dataset, the full report to MANAGER_REPORT.

If no reviews can be collected, the run stops with a clear message and this Actor charges nothing.

---

Input

Field	Description
startUrl	TripAdvisor hotel, restaurant or attraction page URL.
maxReviews	Reviews to collect from the URL (10-500). Default 100.
onlyNewReviews	Monitoring mode for scheduled runs. First run = baseline; later runs for the same URL analyze and charge only new reviews. Default off.
reviews	Alternative: your own reviews as plain strings or {text, rating} objects (for example from Google, Booking.com or guest surveys). Used only when startUrl is empty.
businessName	Property name, used as report context. Filled in automatically in URL mode.
domainContext	Advanced: a focus hint, for example "a family resort; focus on kids' facilities and pool".
language	English, Türkçe, Deutsch, Español, Français
model	Advanced: the default is fast and economical
maxAksiyon	Actions shown in the table (3-10). The full list is in the report.

Example: hotel URL

{
  "startUrl": "https://www.tripadvisor.com/Hotel_Review-gXXXX-dXXXX-Reviews-Your_Hotel.html",
  "maxReviews": 200,
  "language": "English"
}

Example: reviews from any source

{
  "reviews": [
    {"text": "Spotless room and a perfect harbor location.", "rating": 5},
    {"text": "Lovely staff but the street noise kept us up.", "rating": 3},
    "Check-in took forty minutes on a Friday afternoon."
  ],
  "businessName": "Harbor View Hotel"
}

---

Pricing

This Actor charges per event. Current prices are on the Pricing tab; at the time of writing:

Event	When	Price
actor-start	Once per run	$0.0001
reviews-processed-100	Per 100 reviews analyzed (rounded up)	$0.40
report-generated	Once per report	$0.25

In URL mode, the review scraper bills your account separately at its own price. The first source in the chain costs about $0.0005 per review; every call has a spending cap.

Reviews	This Actor	Collection (approx.)	Total (approx.)
50 (your own)	$0.65	$0	$0.65
100 from URL	$0.65	$0.05	$0.70
300 from URL	$1.45	$0.15	$1.60
500 from URL	$2.25	$0.25	$2.50

---

Integrations

API

curl -X POST "https://api.apify.com/v2/acts/enezli~tripadvisor-review-intelligence/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrl":"https://www.tripadvisor.com/Hotel_Review-...html","maxReviews":100}'

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")
run = client.actor("enezli/tripadvisor-review-intelligence").call(
    run_input={"startUrl": "https://www.tripadvisor.com/Hotel_Review-...html", "maxReviews": 100})
report = client.key_value_store(run["defaultKeyValueStoreId"]).get_record("MANAGER_REPORT")["value"]
print(report["executive_summary"])

Weekly or monthly monitoring (only new reviews)

1. Turn on onlyNewReviews and save the input as a task for each property URL.
2. Add a schedule to the task (weekly suits most teams; daily for busy listings).
3. The first run analyzes every review and stores it as the baseline.
4. Each later run collects the latest reviews, skips the ones it has already seen, and builds the action plan from new reviews only. MANAGER_REPORT.monitoring shows new_reviews and new_negative_reviews (1-2 stars), so you can alert on bad weeks.
5. A week with no new reviews returns one "No new reviews" row and costs only the start fee. You never pay twice for the same review.

Seen reviews are kept in a named key-value store whose name starts with review-watch- in your own Apify account. Delete it to start a fresh baseline.

n8n, Make, Zapier

Run Actor → read MANAGER_REPORT → post the summary to Slack, append actions to a Google Sheet, or create tasks in your project tool.

AI agents (MCP)

Available through the Apify MCP server, so an assistant can answer "what are guests complaining about at this hotel?" on request.

---

Workflow recipes

Monthly property review. Schedule a run for each property on the first of the month. Send critical_step and the top three actions to the management meeting agenda. Keep the reports; the history shows which fixes moved the rating.

Competitive set benchmark. Run the same settings on your five closest competitors each quarter. Put their top_complaints and top_praises side by side. Where they are weak and you are strong, promote it; where they are strong and you are weak, plan it.

Pre-renovation evidence. Before a capex request, run on the last 300 reviews and export the actions about rooms, bathrooms or noise with their theme counts. Owners approve budgets faster with counted guest evidence.

New manager onboarding. Give a new department head the latest report on day one. It summarizes what guests value and what frustrates them faster than any handover meeting.

---

Review reply checklist

• Reply to recent reviews that mention the top complaint, with what is being done
• Thank reviewers who mention a top praise by name of the staff member or feature
• Keep replies specific; avoid a single template for every review
• Brief front-line staff on the top three complaints this month
• Update your website and OTA descriptions with the top praises, in guests' own words
• Re-check the themes after changes to confirm improvement

---

Glossary

• Theme: a recurring topic such as cleanliness, staff, noise, breakfast or value, with frequency and direction.
• Risk of inaction: what will likely happen to reviews and rating if nothing changes.
• Benefit / Cost: estimates used to rank actions.
• Score: the combined priority used to sort the table.
• Quick win: a low-cost action with visible effect for guests.
• Critical step: the one action to do first.
• Competitor opportunity: a gap in the guest experience that you or a competitor can use.

---

Tips for better results

• Use 100-300 reviews. Fewer than 30 gives thin themes.
• Add a domainContext for special property types (boutique, family resort, fine dining).
• Benchmark three to five competitors with the same settings.
• Choose your team's language; guest reviews in any language are understood.
• Re-run after changes and compare themes to measure impact.

What the report will not do

• It does not post replies to TripAdvisor or contact reviewers.
• It does not change your listing or access your management account.
• It does not judge whether a single review is fake; it looks for patterns across many reviews, which makes one-off outliers matter less.

Limitations

• Review availability depends on TripAdvisor and on the scraper sources; some pages return fewer reviews than requested.
• Benefit, cost and risk are model estimates from review content, not financial calculations.
• The analysis reflects the reviews collected; very recent changes may not show yet.

---

Troubleshooting

Symptom	Cause	Fix
"No reviews could be collected from this URL"	A review source failed for that page; the message lists which one and why	Check the URL opens a public TripAdvisor page; try again later. This Actor charged nothing
"This page has no public reviews yet"	Every review source finished normally and found 0 reviews (common for newly listed hotels and restaurants)	Run it again once guests have reviewed it. This Actor charged nothing
"No valid reviews found"	The pasted reviews list was empty or malformed	Paste reviews as {"text": ..., "rating": ...} objects, or use a URL
Fewer reviews than requested	The page has fewer reviews, or a partial result	Normal; the log shows which sources were tried
Themes feel generic	Very small sample	Increase maxReviews
Report in the wrong language	language left at English	Choose the output language

---

FAQ

Do I need a TripAdvisor account or API key? No. Public review pages are collected for you.

How far back do the reviews go? Reviews are collected in the order the source scraper returns them, up to your maxReviews limit. For a wider time window, raise the limit; for a specific period, export reviews for that period and paste them as reviews.

Will guests or the property know I ran an analysis? No. Only public review pages are read; nothing is posted and no one is contacted.

Does it work for restaurants and attractions, not just hotels? Yes. Any TripAdvisor page with reviews works.

Can I analyze Google or Booking.com reviews? Yes, in bring-your-own mode: paste them as reviews. URL collection is for TripAdvisor.

Can I analyze competitors? Yes. Any public TripAdvisor page works.

Am I charged if nothing is collected? No. This Actor charges only after reviews are available for analysis.

Is my data stored? Only in your own Apify storage. Review text is sent to the language model provider solely to produce your report.

Can I get the raw reviews? Yes. In URL mode they are in the scraper's own run in your account (Runs tab).

Does it read reviews in other languages? Yes. Reviews in any language the model understands are analyzed; the report is written in the output language you choose.

Can I run several properties at once? Start one run per property, in parallel if you like, or loop over URLs with the API. Each report stays separate and comparable.

How is this different from TripAdvisor's own management center? The management center shows your ratings and lets you reply. This Actor reads the review text and turns it into prioritized actions, and it works on competitors too.

Why is the price per 100 reviews? Analysis cost grows with review volume. Rounding up per 100 keeps the price simple and predictable before you run.

---

What's new

• Automatic source fallback: if one TripAdvisor review scraper fails or returns too few reviews, the next one is tried, each with a spending cap.
• Split-and-retry analysis: long responses are never silently cut; the chunk is split and analyzed again.
• No charge on empty collection: if no reviews are found, the run stops before any analysis charge.

---

Trademarks

This Actor is not affiliated with, endorsed by, or connected to Tripadvisor. All product names are trademarks of their respective owners.