# Wego Reviews Scraper (`stealth_mode/wego-reviews-scraper`) Actor

Scrape hotel reviews from Wego.com by hotel ID, with control over sorting, pagination, and volume. Outputs 13 structured fields including ratings, review content, author info, and provider metadata — perfect for hospitality analytics and reputation monitoring.

- **URL**: https://apify.com/stealth\_mode/wego-reviews-scraper.md
- **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community)
- **Categories:** Automation, Developer tools, Travel
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 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/platform/actors/running/actors-in-store#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

## Wego.com Hotel Reviews Scraper: Extract Guest Reviews at Scale

***

### What Is Wego.com?

Wego.com is a travel metasearch platform popular across Asia-Pacific and the Middle East, aggregating hotel prices and guest reviews from multiple providers. Its review data — sourced from various booking platforms — offers valuable signals for reputation analysis, competitive benchmarking, and sentiment research. Manually collecting this data is impractical at scale; the **Wego.com Reviews Scraper** automates extraction with flexible filtering and pagination.

***

### Overview

The **Wego Hotel Reviews Scraper** collects guest review records for any hotel listed on Wego.com, identified by its numeric Hotel ID. It supports:

- **Reputation managers** monitoring guest sentiment across providers
- **Data analysts** building review datasets for NLP or sentiment modeling
- **Hospitality researchers** comparing ratings across properties or regions
- **Developers** feeding review data into dashboards or aggregator platforms

***

### Input Format

```json
{
  "hotel_id": "1028684",
  "sort_by": "posted_at,desc",
  "page": 2,
  "max_items_per_url": 200,
  "ignore_url_failures": true
}
```

| Field | Type | Description |
|---|---|---|
| `hotel_id` | `string` | **Required.** The numeric Hotel ID from the Wego URL. Example: `.../1028684` → `"1028684"` |
| `sort_by` | `string` | Sort order for reviews. Options: `"posted_at,desc"` (Latest), `"rating,desc"` (High rating first), `"rating,asc"` (Low rating first) |
| `page` | `integer` | Page number to start scraping from. Default: `1`. Use `2`+ to skip earlier pages or resume a run |
| `max_items_per_url` | `integer` | Maximum number of reviews to collect. Default: `20`. Set higher (e.g., `200`) for bulk extraction |
| `ignore_url_failures` | `boolean` | If `true`, the scraper continues running even if a page fails. Recommended: `true` for large runs |

**Finding your Hotel ID:**\
Open a hotel on Wego.com. The URL pattern is:\
`hotels/searches/lon/2026-05-26/2026-05-27/`**`1028684`**\
The trailing number is your `hotel_id`.

***

### Output Format

**Sample record:**

```json
{
  "id": "expedia.com_1651839863_1028684",
  "hotel_id": 1028684,
  "provider_code": "expedia.com",
  "provider_review_id": "1651839863",
  "provider_hotel_url": null,
  "wego_review_id": 2022,
  "locale": "en",
  "title": "Awesome Hotel",
  "rating": 10.0,
  "posted_at": "2022-05-06",
  "updated_at": "2026-05-26",
  "contents": [
    {
      "type": "neutral",
      "comment": "They stay here was amazing! The staff was very friendly and always checking up on us. Their bar and restaurant was really good. We got a pizza and a chicken blue (not 100% sure on the name, but look at the pic). Their gym has an awesome view. \n\nThis was my first time in London and I had an awesome time! And this hotel was a big part. Good job team!\n\nFinally, this hotel is walking distance from Dadas Diner, which is a restaurant I really recommend. The walk there is nice!"
    }
  ],
  "author": {
    "type": "extended_group",
    "type_en": "extended_group",
    "name": "Martin",
    "travel_purpose": "leisure",
    "traveller_type": "Group",
    "traveller_type_en": "Group",
    "country": null,
    "is_anonymous": null
  },
  "from_url": "https://srv.wego.com/hotel-management/api/provider-reviews/v2/search?app_type=WEB_APP&locale=en&per_page=100&page=2&sorts=score_desc&hotel_id=1028684"
}
```

Each review returns 13 fields:

#### Identifiers

| Field | Meaning |
|---|---|
| `ID` | Internal scraper record ID |
| `Hotel ID` | Wego hotel identifier matching your input |
| `Wego Review ID` | Wego's own unique review identifier |
| `Provider Review ID` | Original review ID from the source booking platform |
| `Provider Code` | Code identifying the review source provider (e.g., Booking.com, Expedia) |
| `Provider Hotel URL` | URL of the hotel listing on the originating provider's site |

#### Review Content

| Field | Meaning |
|---|---|
| `Title` | Headline of the review as written by the guest |
| `Rating` | Numeric score given by the reviewer |
| `Contents` | Full text body of the review |
| `Locale` | Language/region of the reviewer (e.g., `en_US`, `ar_AE`) |

#### Timestamps & Author

| Field | Meaning |
|---|---|
| `Posted At` | Date the review was originally published |
| `Updated At` | Date the review was last modified |
| `Author` | Reviewer name or anonymized identifier |
-----------------------------------------------------

### How to Use

1. **Locate the Hotel ID** — Open the target hotel on Wego.com and extract the numeric ID from the URL.
2. **Set sort order** — Choose `posted_at,desc` for latest reviews, or `rating,asc` to surface the most critical feedback first.
3. **Configure pagination** — Set `page: 1` to start from the beginning, or a higher value to resume from a specific page.
4. **Set volume** — Use `max_items_per_url` to cap collection. Set `200`+ for comprehensive datasets.
5. **Run and export** — Download results as JSON or CSV for analysis.

**Tips:**

- To collect all reviews, run multiple times incrementing `page` and combining results.
- Use `sort_by: "rating,asc"` to prioritize negative reviews for complaint analysis.
- `ignore_url_failures: true` is recommended for multi-page runs to avoid interruptions on empty pages.

***

### Use Cases & Business Value

- **Reputation monitoring:** Track how a property's perceived quality shifts over time
- **Competitive analysis:** Compare sentiment and ratings across competing hotels
- **NLP/sentiment modeling:** Build labeled datasets for machine learning pipelines
- **Provider attribution:** Identify which booking platform drives the most reviews via `Provider Code`

***

### Conclusion

The **Wego.com Hotel Reviews Scraper** delivers clean, structured review data with provider-level attribution and flexible sorting — without manual browsing. Whether you're monitoring a single property or building a multi-hotel dataset, it provides the depth needed for meaningful hospitality intelligence.

# Actor input Schema

## `hotel_id` (type: `string`):

Enter Hotel ID. For example, hotels/searches/lon/2026-05-26/2026-05-27/1028684 -> 1028684

## `sort_by` (type: `string`):

Select your option to sort reviews

## `page` (type: `integer`):

Page to start from

## `ignore_url_failures` (type: `boolean`):

If true, the scraper will continue running even if some URLs fail to be scraped.

## `max_items_per_url` (type: `integer`):

The maximum number of items to scrape per URL.

## Actor input object example

```json
{
  "hotel_id": "1028684",
  "page": 1,
  "ignore_url_failures": true,
  "max_items_per_url": 20
}
```

# 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 = {
    "hotel_id": "1028684",
    "page": 1,
    "ignore_url_failures": true,
    "max_items_per_url": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("stealth_mode/wego-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 = {
    "hotel_id": "1028684",
    "page": 1,
    "ignore_url_failures": True,
    "max_items_per_url": 20,
}

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

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

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

```

## CLI example

```bash
echo '{
  "hotel_id": "1028684",
  "page": 1,
  "ignore_url_failures": true,
  "max_items_per_url": 20
}' |
apify call stealth_mode/wego-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=stealth_mode/wego-reviews-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Q5pOMaOlRVP35sJVG/builds/t5VgKQdx0eDb726a6/openapi.json