# Analyze hair and beauty salon reviews: result, price, staff

**Use case:** 

Get, per salon, what clients praise or criticize (result, welcome, price, punctuality, hygiene), the severity of each complaint, the share of negative reviews over the last 90 days and the complaints still waiting for a reply. Works with pasted reviews or the dataset of a reviews scraper. The sample uses fictional reviews.

## Input

```json
{
  "reviews": [
    {
      "text": "Exactly the balayage I asked for, and Chloe took time to explain the aftercare.",
      "rating": 5,
      "placeName": "Studio Lumière (sample)",
      "category": "Hair salon",
      "date": "2026-09-05"
    },
    {
      "text": "The price doubled at the till compared to the website and nobody warned me.",
      "rating": 1,
      "placeName": "Studio Lumière (sample)",
      "category": "Hair salon",
      "date": "2026-09-22"
    },
    {
      "text": "Lovely welcome, coffee offered, but I waited 30 minutes before they started.",
      "rating": 3,
      "placeName": "Studio Lumière (sample)",
      "category": "Hair salon",
      "date": "2026-09-30"
    },
    {
      "text": "The brushes and towels did not look clean at all.",
      "rating": 2,
      "placeName": "Studio Lumière (sample)",
      "category": "Hair salon",
      "date": "2026-10-02"
    },
    {
      "text": "Perfect cut, fair price, I will be back.",
      "rating": 5,
      "placeName": "Studio Lumière (sample)",
      "category": "Hair salon",
      "date": "2026-08-18",
      "reply": "Thanks a lot, see you soon!"
    },
    {
      "text": "My colour faded in a week and they refused to redo it.",
      "rating": 2,
      "placeName": "Studio Lumière (sample)",
      "category": "Hair salon",
      "date": "2026-07-29"
    }
  ],
  "businessType": "beauty",
  "maxReviews": 500,
  "maxReviewsPerPlace": 100,
  "includeReviewText": true
}
```

## Output

```json
{
  "placeName": {
    "label": "Business",
    "format": "string"
  },
  "reviewsAnalyzed": {
    "label": "Reviews",
    "format": "integer"
  },
  "averageRating": {
    "label": "Rating",
    "format": "number"
  },
  "negativeShare": {
    "label": "Negative share",
    "format": "number"
  },
  "unansweredComplaints": {
    "label": "Unanswered complaints",
    "format": "integer"
  },
  "summary": {
    "label": "Summary",
    "format": "string"
  }
}
```

## How it works

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

The Review Analyzer API — Sentiment, Topics & Complaints Actor is ready to run with the inputs already set for "Analyze hair and beauty salon reviews: result, price, staff". [Sign up or log in](https://console.apify.com/create-task-from-example/dUdOexfGo7sj8Xn6a) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Analyze hair and beauty salon reviews: result, price, staff" task

The Review Analyzer API — Sentiment, Topics & Complaints Actor will start running based on the input automatically. You can also change all the input fields, like reviews, business type, and more, to match your specific use case.

### 3. Receive the "Analyze hair and beauty salon reviews: result, price, staff" 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 business, reviews, 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 "Analyze hair and beauty salon reviews: result, price, staff" task via API](https://apify.com/sherwood/review-analyzer.md).

## About this Actor

This example demonstrates how to use [Review Analyzer API — Sentiment, Topics & Complaints](https://apify.com/sherwood/review-analyzer.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/sherwood/review-analyzer.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/sherwood/review-analyzer.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`).