# Tripadvisor Restaurant Reviews Scraper (`kawsar/tripadvisor-restaurant-reviews-scraper`) Actor

Tripadvisor restaurant reviews scraper that collects ratings, review text, visitor details, and owner replies so SEO and reputation teams can track restaurant feedback at scale.

- **URL**: https://apify.com/kawsar/tripadvisor-restaurant-reviews-scraper.md
- **Developed by:** [Kawsar](https://apify.com/kawsar) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.99 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Tripadvisor Restaurant Reviews Scraper: Extract Restaurant Reviews for SEO and Local Research

Tripadvisor Restaurant Reviews Scraper is an Apify Actor that collects guest reviews from Tripadvisor restaurant pages. Paste one or more `Restaurant_Review` URLs and get structured review data: ratings, titles, body text, trip type, visitor details, category scores, photos, and owner replies when they exist.

This actor is built for SEO teams, local search work, reputation monitoring, and competitor research. Export results as JSON, CSV, Excel, XML, or HTML, or pull them through the Apify API into your own pipeline.

No proxy configuration is required.

***

### Why use this actor?

Tripadvisor is one of the main public sources of restaurant reputation signals. Manual copying does not scale when you track many locations, languages, or competitors.

With this actor you can:

- Collect Tripadvisor restaurant reviews in bulk from listing pages
- Keep star ratings plus Value / Service / Food / Atmosphere scores when shown
- Capture reviewer name, hometown, and contribution count
- Include owner or manager replies only when Tripadvisor actually shows one
- Cap how many reviews you collect per run with Max items
- Schedule runs on Apify for weekly or monthly monitoring

***

### What does Tripadvisor Restaurant Reviews Scraper do?

1. Accepts Tripadvisor restaurant URLs (`Restaurant_Review-...`)
2. Opens each reviews page and follows pagination (`-or15-`, `-or30-`, …)
3. Parses each review card on the page
4. Attaches restaurant metadata (name, address, cuisine, aggregate rating)
5. Adds `ownerResponseText` / `ownerResponseDate` only when a management reply is present
6. Pushes one dataset item per review

Invalid non-restaurant URLs are skipped with a warning.

***

### What data does this actor extract?

Each successful dataset row is one review.

| Field | Type | Description |
| --- | --- | --- |
| `reviewId` | string | Tripadvisor review id |
| `reviewUrl` | string | Direct link to the review |
| `reviewTitle` | string | Review headline |
| `reviewText` | string | Full review body |
| `rating` | integer | Overall bubble rating (1-5) |
| `publishedDate` | string | Written date shown on the page |
| `visitDate` | string | Visit / dining month when shown |
| `tripType` | string | Couples, Family, Friends, Solo, or Business |
| `language` | string | Detected language code when available |
| `helpfulVotes` | integer | Helpful vote count when shown |
| `photoUrls` | array | Photo URLs attached to the review |
| `subratings` | object | Category scores: value, service, food, atmosphere |
| `username` | string | Reviewer display name |
| `userProfileUrl` | string | Reviewer profile URL |
| `userLocation` | string | Reviewer hometown |
| `userContributions` | integer | Contribution count from the profile snippet |
| `userAvatarUrl` | string | Reviewer avatar image URL |
| `ownerResponseText` | string | Owner/manager reply text (**only if a reply exists**) |
| `ownerResponseDate` | string | Owner reply date (**only if a reply exists**) |
| `restaurantName` | string | Restaurant name |
| `restaurantUrl` | string | Restaurant page URL |
| `restaurantLocationId` | string | Tripadvisor geo id (`g`) |
| `restaurantId` | string | Tripadvisor restaurant id (`d`) |
| `cuisine` | string | Cuisine list when available |
| `priceRange` | string | Price range |
| `aggregateRating` | string | Overall restaurant score |
| `restaurantReviewCount` | string | Total reviews listed for the place |
| `address` | string | Restaurant address |
| `scrapedAt` | string | UTC collection timestamp |
| `error` | string | Present only when a URL fails |

#### Owner reply fields

Not every Tripadvisor review has a management response.

- If the page includes an owner/manager reply, the actor returns `ownerResponseText` and `ownerResponseDate`.
- If there is no reply, those two fields are **omitted** from the item. They are not filled with `null`.

That keeps the dataset cleaner for SEO exports, spreadsheets, and API consumers.

***

### How to scrape Tripadvisor restaurant reviews

1. Open **Tripadvisor Restaurant Reviews Scraper** on Apify.
2. Paste one or more Tripadvisor `Restaurant_Review` URLs into **Restaurant URLs**.
3. Set **Max items** to control how many reviews are collected.
4. Optionally filter by language or minimum rating.
5. Click **Start**.
6. Download the dataset or call the Apify API when the run finishes.

#### Example input

```json
{
    "startUrls": [
        "https://www.tripadvisor.com/Restaurant_Review-g608676-d2062969-Reviews-Arlberger_Dorfstubn-St_Anton_am_Arlberg_Tirol_Austrian_Alps.html"
    ],
    "maxItems": 15,
    "language": "en",
    "minRating": 1,
    "requestTimeoutSecs": 60
}
```

#### Example output (no owner reply)

```json
{
    "reviewId": "1071729054",
    "reviewUrl": "https://www.tripadvisor.com/ShowUserReviews-g608676-d2062969-r1071729054-Arlberger_Dorfstubn-St_Anton_am_Arlberg_Tirol_Austrian_Alps.html",
    "reviewTitle": "Very good",
    "reviewText": "Great food, very nice service!",
    "rating": 5,
    "publishedDate": "August 6, 2026",
    "visitDate": "Aug 2026",
    "tripType": "Couples",
    "language": "en",
    "helpfulVotes": 0,
    "photoUrls": [],
    "subratings": {
        "value": 5,
        "service": 5,
        "food": 5,
        "atmosphere": 5
    },
    "username": "Zsuzsanna K",
    "userProfileUrl": "https://www.tripadvisor.com/Profile/68zsuzsannak",
    "userLocation": "Budapest, Hungary",
    "userContributions": 1,
    "restaurantName": "Arlberger Dorfstubn",
    "restaurantUrl": "https://www.tripadvisor.com/Restaurant_Review-g608676-d2062969-Reviews-Arlberger_Dorfstubn-St_Anton_am_Arlberg_Tirol_Austrian_Alps.html",
    "restaurantLocationId": "608676",
    "restaurantId": "2062969",
    "cuisine": "Austrian, European",
    "aggregateRating": "3.8",
    "restaurantReviewCount": "217",
    "address": "Dorfstrasse 60, St. Anton am Arlberg, Austrian Alps, 6580, AT",
    "scrapedAt": "2026-09-13T12:00:00+00:00"
}
```

#### Example output (with owner reply)

```json
{
    "reviewId": "991861538",
    "reviewTitle": "Great dinner",
    "reviewText": "Friendly staff and excellent local dishes.",
    "rating": 5,
    "username": "Traveler123",
    "restaurantName": "Example Restaurant",
    "ownerResponseText": "Thank you for dining with us. We look forward to welcoming you again.",
    "ownerResponseDate": "January 12, 2026",
    "scrapedAt": "2026-09-13T12:00:00+00:00"
}
```

***

### Input parameters

| Field | Type | Required | Default | Description |
| --- | --- | --- | --- | --- |
| `startUrls` | array of strings | yes | | Tripadvisor restaurant review page URLs (`Restaurant_Review`) |
| `maxItems` | integer | no | `15` | Maximum reviews to collect in one run (1-1000) |
| `language` | string | no | empty | Optional language filter such as `en` or `de` |
| `minRating` | integer | no | empty | Keep reviews with this bubble rating or higher (1-5) |
| `requestTimeoutSecs` | integer | no | `60` | Per-request timeout in seconds (15-120) |

#### URL requirements

Accepted:

```text
https://www.tripadvisor.com/Restaurant_Review-gXXXXX-dYYYYY-Reviews-Name-City.html
```

Not accepted:

- Hotel review URLs (`Hotel_Review`)
- Attraction review URLs (`Attraction_Review`)
- Generic Tripadvisor search or city pages

***

### Pagination and limits

Tripadvisor restaurant review pages typically show 15 reviews at a time. The actor follows offset URLs such as:

- `...-Reviews-...` (first page)
- `...-Reviews-or15-...`
- `...-Reviews-or30-...`

Collection stops when:

- `maxItems` is reached for the run, or
- no further review page is available

Use the default of 15 while testing. Raise `maxItems` once the output shape looks right.

***

### Use cases

- **Local SEO**: pull review themes, rating trends, and common phrases for restaurant landing pages
- **Reputation monitoring**: schedule runs and watch new Tripadvisor restaurant reviews over time
- **Owner reply tracking**: see which reviews received a management response and which did not
- **Competitor research**: compare nearby restaurants on food, service, value, and atmosphere
- **Sentiment / NLP datasets**: feed review text into classification or reporting tools
- **Agency reporting**: export client restaurant feedback without manual scraping

***

### Integrations

You can run this actor from:

- Apify Console (manual runs and schedules)
- Apify API / Apify client (Python, JavaScript, REST)
- Make, Zapier, n8n, or any webhook that can start an Actor run
- Downstream jobs that read the default dataset URL after the run finishes

Typical workflow:

1. Schedule the actor daily or weekly
2. Keep `maxItems` modest and filter by date in your own warehouse if needed
3. Append new reviews to a sheet, CRM, or SEO dashboard

***

### Best practices

- Start with 1 restaurant URL and `maxItems: 15` to verify parsing
- Prefer full `Restaurant_Review` URLs, including the `-Reviews-` segment
- Use `language` only when you need a single language; leave it empty for mixed results
- Use `minRating` for complaint mining (`1` or `2`) or praise sampling (`5`)
- For large multi-location jobs, split URLs across runs to stay within `maxItems`

***

### FAQ

**Does this work only for restaurants?**
Yes. Input URLs should be Tripadvisor `Restaurant_Review` pages. Hotel and attraction URLs are skipped.

**Why are `ownerResponseText` and `ownerResponseDate` missing on some rows?**
Those fields are included only when Tripadvisor shows an owner or manager reply on that review. If there is no reply, the fields are left out on purpose instead of returning `null`.

**Can I scrape multiple restaurants in one run?**
Yes. Add several URLs to `startUrls`. `maxItems` caps the total number of reviews saved.

**How many reviews can I get per run?**
Up to 1000 total (`maxItems`). The default is 15. Practical volume also depends on how many reviews the restaurant actually has.

**Do I need to set up proxies?**
No. Proxy setup is not required for this actor.

**What export formats are supported?**
JSON, CSV, Excel, XML, and HTML from the Apify dataset UI, plus API access to dataset items.

**Can I filter by language or rating?**
Yes. Use `language` and/or `minRating` in the input.

**What happens if a page fails?**
The actor logs the error, pushes a small error item with `restaurantUrl` and `error`, and continues with the next URL.

***

### Related Tripadvisor tools

Pair this reviews scraper with other Tripadvisor actors from the same publisher:

- [Tripadvisor Restaurant Listings Extractor](https://apify.com/kawsar/tripadvisor-restaurant-listings-extractor): collect restaurant listing data
- [Tripadvisor Hotels Extractor](https://apify.com/kawsar/tripadvisor-hotels-extractor): collect hotel listing data

This actor focuses on restaurant review pages for SEO, reputation, and local research workflows.

***

### Output tips for SEO teams

- Track `aggregateRating` and `restaurantReviewCount` alongside individual reviews
- Use `subratings` to see whether complaints cluster on service, food, value, or atmosphere
- Keep `reviewUrl` for citation and verification
- Treat missing owner-reply fields as “no public response,” not as a scraper error

Tripadvisor Restaurant Reviews Scraper turns restaurant review pages into structured data you can sort, filter, and feed into SEO tools without copying Tripadvisor by hand.

# Actor input Schema

## `startUrls` (type: `array`):

One or more Tripadvisor Restaurant\_Review page URLs. Paste full restaurant URLs, one per line.

## `maxItems` (type: `integer`):

Maximum number of reviews to collect in one run across all restaurant URLs.

## `language` (type: `string`):

Optional language code filter (for example en). Leave empty to keep all languages found on the page.

## `minRating` (type: `integer`):

Only keep reviews with this bubble rating or higher (1-5). Leave empty for all ratings.

## `requestTimeoutSecs` (type: `integer`):

Per-request timeout in seconds. Tripadvisor pages can be heavy, so 60 is a safe default.

## Actor input object example

```json
{
  "startUrls": [
    "https://www.tripadvisor.com/Restaurant_Review-g608676-d2062969-Reviews-Arlberger_Dorfstubn-St_Anton_am_Arlberg_Tirol_Austrian_Alps.html"
  ],
  "maxItems": 15,
  "language": "en",
  "requestTimeoutSecs": 60
}
```

# Actor output Schema

## `reviews` (type: `string`):

Dataset of Tripadvisor restaurant reviews with ratings, text, visitor details, and owner replies.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "startUrls": [
        "https://www.tripadvisor.com/Restaurant_Review-g608676-d2062969-Reviews-Arlberger_Dorfstubn-St_Anton_am_Arlberg_Tirol_Austrian_Alps.html"
    ],
    "maxItems": 15
};

// Run the Actor and wait for it to finish
const run = await client.actor("kawsar/tripadvisor-restaurant-reviews-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "startUrls": ["https://www.tripadvisor.com/Restaurant_Review-g608676-d2062969-Reviews-Arlberger_Dorfstubn-St_Anton_am_Arlberg_Tirol_Austrian_Alps.html"],
    "maxItems": 15,
}

# Run the Actor and wait for it to finish
run = client.actor("kawsar/tripadvisor-restaurant-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "startUrls": [
    "https://www.tripadvisor.com/Restaurant_Review-g608676-d2062969-Reviews-Arlberger_Dorfstubn-St_Anton_am_Arlberg_Tirol_Austrian_Alps.html"
  ],
  "maxItems": 15
}' |
apify call kawsar/tripadvisor-restaurant-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,kawsar/tripadvisor-restaurant-reviews-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/IzStD7G3GVgpS1My5/builds/g1lP3HVVvTmc9ZYT3/openapi.json