# Download Agoda Reviews to CSV

**Use case:** 

The full export: five hundred reviews of one property, each with the numeric score, the score band, the title, the separated positives and negatives, the room type booked, the stay dates, the reviewer country and any management response. Download as CSV or JSON, or read it over the API. Cost: 500 review rows at $0.005 = at most $2.50 a run.

## Input

```json
{
  "startUrls": [
    "https://www.agoda.com/tivoli-avenida-liberdade-lisboa/hotel/lisbon-pt.html"
  ],
  "hotelIds": [],
  "hotelNames": [],
  "maxReviewsPerHotel": 500,
  "reviewsSort": "most_recent",
  "maxRating": 0,
  "requireText": false,
  "locale": "en-us",
  "includeHotelRow": true,
  "sessions": 4,
  "perIp": 1,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

## Output

```json
{
  "hotel_name": {
    "label": "Hotel name",
    "format": "string"
  },
  "rating": {
    "label": "Rating",
    "format": "number"
  },
  "rating_5": {
    "label": "Rating 5",
    "format": "number"
  },
  "rating_text": {
    "label": "Rating text",
    "format": "string"
  },
  "title": {
    "label": "Title",
    "format": "string"
  },
  "text": {
    "label": "Text",
    "format": "string"
  },
  "positives": {
    "label": "Positives",
    "format": "string"
  },
  "negatives": {
    "label": "Negatives",
    "format": "string"
  },
  "language": {
    "label": "Language",
    "format": "string"
  },
  "review_date_text": {
    "label": "Review date text",
    "format": "string"
  },
  "check_in": {
    "label": "Check in",
    "format": "string"
  },
  "check_out": {
    "label": "Check out",
    "format": "string"
  },
  "room_type": {
    "label": "Room type",
    "format": "string"
  },
  "reviewer_name": {
    "label": "Reviewer name",
    "format": "string"
  },
  "reviewer_country": {
    "label": "Reviewer country",
    "format": "string"
  },
  "response": {
    "label": "Response",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Agoda Reviews Scraper — Hotel Guest Reviews & Ratings](https://apify.com/kestrel/agoda-reviews-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/kestrel/agoda-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`.
- **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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/kestrel/agoda-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).