# Booking.com Competitor Reviews: Las Vegas Strip

**Use case:** 

A comp set as a quality or revenue manager reads it: three Strip resorts side by side, thirty newest reviews each, plus a free hotel row per property carrying Booking's seven category scores (staff, facilities, cleanliness, comfort, value, location, Wi-Fi) and the review count. The hotels view puts the scores in one table. Cost: 90 review rows at $0.005 = at most $0.45 a run.

## Input

```json
{
  "startUrls": [],
  "hotelNames": [
    "Bellagio Las Vegas",
    "The Venetian Las Vegas",
    "Caesars Palace Las Vegas"
  ],
  "hotelIds": [],
  "maxReviewsPerHotel": 30,
  "reviewsSort": "most_recent",
  "languages": [],
  "travelerType": "all",
  "keyword": "",
  "maxRating": 0,
  "requireText": false,
  "locale": "en-US",
  "includeHotelRow": true,
  "sessions": 4,
  "perIp": 1,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

## Output

```json
{
  "hotel_id": {
    "label": "Hotel id",
    "format": "string"
  },
  "hotel_name": {
    "label": "Hotel name",
    "format": "string"
  },
  "city": {
    "label": "City",
    "format": "string"
  },
  "country": {
    "label": "Country",
    "format": "string"
  },
  "review_count": {
    "label": "Review count",
    "format": "integer"
  },
  "score_staff": {
    "label": "Score staff",
    "format": "number"
  },
  "score_facilities": {
    "label": "Score facilities",
    "format": "number"
  },
  "score_cleanliness": {
    "label": "Score cleanliness",
    "format": "number"
  },
  "score_comfort": {
    "label": "Score comfort",
    "format": "number"
  },
  "score_value": {
    "label": "Score value",
    "format": "number"
  },
  "score_location": {
    "label": "Score location",
    "format": "number"
  },
  "score_wifi": {
    "label": "Score wifi",
    "format": "number"
  },
  "languages": {
    "label": "Languages",
    "format": "array"
  },
  "traveler_types": {
    "label": "Traveler types",
    "format": "array"
  },
  "reviews_fetched": {
    "label": "Reviews fetched",
    "format": "integer"
  }
}
```

## About this Actor

This example demonstrates how to use [Booking.com Reviews Scraper — Hotel Guest Reviews & Ratings](https://apify.com/kestrel/booking-reviews-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/kestrel/booking-reviews-scraper.md) to learn more, explore other use cases, and run it yourself.


## 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.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **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`.
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- **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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/kestrel/booking-reviews-scraper.md

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).