Hotels, restaurants & attractionsCollect the public Tripadvisor reviews of a hotel, restaurant or attraction and the places it competes with. Each review comes as written, with Tripadvisor's English translation alongside, so you can compare markets in one table.
Try these examples for marketing, growth and competitor research.
Collect six months of reviews for your hotel and four nearby competitors. Compare average ratings and sub-ratings for rooms, service and value to see where each property leads.
Keep a benchmark table by property, with links to the reviews behind each score.
Collect reviews in every language and use the English translations to read them together. Look for topics that come up more often in one market, such as breakfast or check-in.
Write a short guest experience brief by market, quoting translated reviews.
See which negative reviews received a management response, who wrote it and how quickly. Compare with competitors and pick examples worth following.
Keep a response log with reply dates and the responder’s role.
FROM FIRST RUN TO REPEATABLE WORKFLOW
{
"places": [
"https://www.tripadvisor.com/Hotel_Review-g186338-d187591-Reviews-The_Ritz_London_Hotel-London_England.html"
],
"maxReviewsPerPlace": 100
}Paste this into the Actor’s JSON input editor. Replace the example targets with yours before running.
Check the current input form on ApifyGive the scraper a Tripadvisor link, a location ID or a place name. Links and IDs point to one place; names can match several. Every review comes as written, with Tripadvisor’s English translation alongside, and the full history back to the first review is available.
| Search method | When to use it | What changes |
|---|---|---|
| Tripadvisor links | When to use itYou already configured the search on the source website. | What changesA link from tripadvisor.com, .co.uk, .de or any other Tripadvisor site gives the same place and reviews. It is the clearest way to name one place. |
| Location IDs | When to use itYou know the exact entity you want to collect. | What changesThe location ID is the d number in a Tripadvisor link, such as d187591. It is short and stable, which suits a saved watchlist. |
| Place names | When to use itYou want to find relevant results before choosing specific targets. | What changesA name reads every place Tripadvisor’s search finds under it, biggest first. Ritz London gives the hotel and several Ritz restaurants. Check place_name, or paste a link to get one place. |
Every review comes in the language it was written in, with Tripadvisor’s English translation in title_english and text_english. Read the English versions to compare markets, and quote the original text in reports.
Compare the related scraperUse the exact field names below in JSON. In Apify’s form, enter list items separately, choose filters, and keep numbers and booleans in their proper types.
Default and prefill are different. A default applies when you omit a setting; a prefill is an example already entered in Apify’s form. Review prefilled targets and limits before every run. Some settings have no schema default. You still need to supply at least one supported target.
placesOne place per line: a Tripadvisor link to a hotel, restaurant, attraction or tour from any country’s Tripadvisor, its location ID (d187591), or its name. A name stands for every place Tripadvisor’s search finds under it.
ratingsOnly reviews with these ratings, as strings from 1 (Terrible) to 5 (Excellent). Select 1 and 2 for negative reviews. Empty means every rating.
languagesOnly reviews written in these languages, as codes or names such as en, de or French. Empty means every language: each review in the language it was written in, with Tripadvisor’s English translation alongside.
dateFromOnly reviews published on or after this date. Use YYYY-MM-DD or a relative period such as 30 days or 6 months. With a daily or weekly schedule, a relative date collects only what is new.
tripTypesOnly reviews from these kinds of trips: Business, Couples, Family, Friends or Solo. Many reviewers leave the trip type out, so a filter also drops those reviews. Empty means every review.
searchTextOnly reviews that mention this word or phrase, as Tripadvisor’s own review search finds them, for example breakfast, noise or rooftop. Use one topic per run.
maxReviewsPerPlaceThe newest this many reviews of each place. Start with 100. Empty means every review, back to the first one.
maxReviewsA hard cap on reviews across the whole run, for every target together. Use it to limit runtime and cost. Empty means no overall cap; the per-target limit still applies.
proxyConfigurationThe US residential proxy is the working default. Tripadvisor answers residential exits, Apify’s datacenter proxy also works, and other settings fall back to residential when Tripadvisor refuses them.
resumeSaves progress about every 30 seconds so an Apify restart or migration can continue the current run. Leave it on for normal use.
continueFromLastRunContinues unfinished work from the previous run with matching input. Earlier results remain in that run’s dataset. Keep false for a fresh collection or a recurring snapshot.
This reference follows the Actor’s published input fields. Check the live form before changing a production workflow. Check the current input form on Apify.
Each example is a separate run. Start small, inspect the results, then increase coverage. Update the targets, countries and dates to match your question.
Collect six months of reviews for one hotel by location ID and two competitors by name, up to 300 each. Check place_name before comparing, because a name can also match restaurants inside a hotel.
{
"places": ["d187591", "The Savoy London", "The Langham London"],
"dateFrom": "6 months",
"maxReviewsPerPlace": 300
}Collect the 1- and 2-star reviews of one restaurant from the last 12 months. Check which ones received a management response and how quickly.
{
"places": ["d719141"],
"ratings": ["1", "2"],
"dateFrom": "12 months",
"maxReviewsPerPlace": 200
}Collect reviews that mention breakfast from family and couples trips, written in English, French or German. Compare what each group says, using the English translations to read them together.
{
"places": ["d187591"],
"searchText": "breakfast",
"tripTypes": ["Family", "Couples"],
"languages": ["en", "fr", "de"],
"maxReviewsPerPlace": 200
}Expect one row per review with its rating, text as written, English translation, dates, trip type, sub-ratings, reviewer and management response, plus the place’s rating and address. The run’s SUMMARY record shows how many reviews each place lists, how many matched your filters and how many were collected. Each place’s details are saved as the PLACES record in the key-value store.
resume protects the current run if Apify restarts it. continueFromLastRun continues an earlier run with the same configuration; earlier records stay in the earlier dataset. Combine both datasets for the complete collection, and raise a previously reached result cap when continuing. Start fresh when you want to see what changed today.
Save one configuration above as input.json. Set APIFY_TOKEN to your Apify API token in your terminal, then send the file as the request body.
curl --fail-with-body --request POST \
--url "https://api.apify.com/v2/actors/jmlp~tripadvisor-reviews-scraper/runs" \
--header "Authorization: Bearer $APIFY_TOKEN" \
--header "Content-Type: application/json" \
--data-binary @input.jsonThe response contains a run ID and defaultDatasetId, not finished results. Wait for the run to succeed, set DATASET_ID to that dataset ID, then fetch its items. For large datasets, use limit and offset to page through the export.
curl --fail-with-body \
--url "https://api.apify.com/v2/datasets/$DATASET_ID/items?format=json" \
--header "Authorization: Bearer $APIFY_TOKEN"Change one setting at a time, keep a small cap, and check the run summary before scaling up.
A name reads every place Tripadvisor’s search finds under it, biggest first. Ritz London gives the hotel and several Ritz restaurants. Check place_name, or paste a link to get one place.
Sub-ratings, trip type and travel date are optional on Tripadvisor, and many reviewers leave them out. Missing values are left empty rather than guessed. Report how many reviews each average is based on.
The US residential proxy is the working default. Tripadvisor answers residential exits, Apify’s datacenter proxy also works, and other settings fall back to residential when Tripadvisor refuses them.
Success means the Actor finished handling the request, not that the source returned data. Check SUMMARY.inputProblem, SUMMARY.problem and the log for missing targets, unsupported filters or refused requests. Test one known target with fewer filters.
Check the global limit, per-search or per-page limits, platform coverage and deduplication. Several searches can find the same record. A source’s headline count can include records the public endpoint does not return. Review unfinished jobs before treating the dataset as complete.
Append review_id, place_name, rating, published_at, trip_type and language. Add columns for topic and follow-up, then filter negative reviews without a response.
Read the setupAsk Claude to compare what guests mention at each place, using text_english and citing review_url. Have it mark which points rest on only a few reviews.
Read the setupChart average rating and sub-ratings by month for each place. Add filters for trip type and language, and show how many reviews each figure is based on.
Read the setupKeep reviews keyed by review_id with the collection time. Unnest subratings into a child table and store place snapshots separately so you can follow rating changes.
Read the setup
Inspect jmlp/tripadvisor-reviews-scraper, then collect up to 200 reviews published in the last six months for https://www.tripadvisor.com/Hotel_Review-g186338-d187591-Reviews-The_Ritz_London_Hotel-London_England.html. Summarize what guests praise and criticize using text_english, cite review_url for each point, and report the response rate for 1- and 2-star reviews.Keep the collection time and original IDs with your records. You’ll need them to check where a result came from or compare it with a later run.
Reviews come from guests who chose to write one, so they aren't a representative survey of every visit. Sub-ratings and trip types are optional, and many reviews leave them out. The English versions are Tripadvisor's machine translations, so check the original text before quoting a review. A place name can match several places, so paste a link when you need one exact place.
No. The scraper reads public Tripadvisor reviews as a signed-out visitor. You need an Apify account to run it.
text_english is filled only for reviews written in another language. English reviews need no translation.
Source and current product details: JMLP’s Tripadvisor Reviews Actor on Apify.
Company reviews & replies01Hear what customers say about a brand.
Collect Trustpilot reviews of any company with ratings, full text and the company's replies. Compare what customers praise and complain about.
Organic search results02Find the sites that outrank you.
Track organic results for the searches your buyers make. Follow competitor domains and build a watchlist for your SEO work.
Tell me what you need to collect or understand. I can help with a custom scraper, a pipeline or the analysis.
Start a project