# Benchmark what guests complain about in a market

**Use case:** 

A city market in one run: for every topic the spread of the hotels scores (median, quartiles) and the best and worst hotels, in the TOPIC_BENCHMARK record. Which topic is weak across the market, and who is best at it.

## Input

```json
{
  "searchQueries": [
    "hotels in Prague",
    "4 star hotels in Prague"
  ],
  "hotels": [],
  "maxHotelsPerSearch": 40,
  "maxHotels": 80,
  "minReviews": 10,
  "excludeVacationRentals": true,
  "readHotelPages": true,
  "minMentions": 15,
  "includeReviewSamples": true,
  "language": "en",
  "country": "us",
  "concurrency": 5,
  "proxy": {
    "useApifyProxy": true
  },
  "dryRun": false
}
```

## Output

```json
{
  "name": {
    "label": "Hotel",
    "format": "text"
  },
  "hotelClass": {
    "label": "Stars",
    "format": "number"
  },
  "rating": {
    "label": "Google rating",
    "format": "number"
  },
  "reviewsCount": {
    "label": "Google reviews",
    "format": "number"
  },
  "otherSitesAverage": {
    "label": "Other sites (mean, of 5)",
    "format": "number"
  },
  "ratingGap": {
    "label": "Google minus others",
    "format": "number"
  },
  "praised": {
    "label": "Praised",
    "format": "array"
  },
  "criticised": {
    "label": "Criticised",
    "format": "array"
  },
  "topicsCount": {
    "label": "Topics",
    "format": "number"
  },
  "city": {
    "label": "City",
    "format": "text"
  },
  "googleUrl": {
    "label": "Google Hotels page",
    "format": "link"
  },
  "query": {
    "label": "Search / name",
    "format": "text"
  },
  "scrapedAt": {
    "label": "Scraped at",
    "format": "date"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Hotel Review Insights: Guest Topics, Sentiment & Ratings Actor is ready to run with the inputs already set for "Benchmark what guests complain about in a market". [Sign up or log in](https://console.apify.com/create-task-from-example/tYN6biEhmmL1EUvdL) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Benchmark what guests complain about in a market" task

The Hotel Review Insights: Guest Topics, Sentiment & Ratings Actor will start running based on the input automatically. You can also change all the input fields, like searches, hotels, and more, to match your specific use case.

### 3. Receive the "Benchmark what guests complain about in a market" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as hotel, stars, google rating, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Benchmark what guests complain about in a market" task via API](https://apify.com/aleksandrbooking/hotel-review-insights.md).

## About this Actor

This example demonstrates how to use [Hotel Review Insights: Guest Topics, Sentiment & Ratings](https://apify.com/aleksandrbooking/hotel-review-insights.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/aleksandrbooking/hotel-review-insights.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

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

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/aleksandrbooking/hotel-review-insights.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).