# Find Gangnam Restaurant Reviews on Naver Place

**Use case:** 

Find Gangnam restaurants on Naver Place and collect visitor reviews, linked blog posts, and rating statistics for restaurant owners and food businesses assessing customer sentiment. Records include review ratings, visit dates, owner replies, rating distributions, and review themes. Change searchKeywords to explore another area or category.

## Input

```json
{
  "placeUrls": [
    "https://map.naver.com/p/entry/place/38239053"
  ],
  "searchKeywords": [
    "강남 맛집"
  ],
  "maxPlacesPerKeyword": 3,
  "maxReviews": 100,
  "includeVisitorReviews": true,
  "includeRatingOnlyReviews": false,
  "includeBlogReviews": false,
  "maxBlogReviews": 10,
  "includeReviewPhotos": false,
  "includeReviewStats": false,
  "maxConcurrency": 3,
  "maxItems": 3
}
```

## Output

```json
{
  "reviewType": {
    "label": "Type",
    "format": "string"
  },
  "placeName": {
    "label": "Place",
    "format": "string"
  },
  "searchKeyword": {
    "label": "Keyword",
    "format": "string"
  },
  "reviewRating": {
    "label": "Rating",
    "format": "number"
  },
  "reviewText": {
    "label": "Review",
    "format": "string"
  },
  "blogTitle": {
    "label": "Blog Post",
    "format": "string"
  },
  "blogDate": {
    "label": "Blog Date",
    "format": "string"
  }
}
```

## How it works

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

The Naver Place Visitor & Blog Review Finder Actor is ready to run with the inputs already set for "Find Gangnam Restaurant Reviews on Naver Place". [Sign up or log in](https://console.apify.com/create-task-from-example/XaHCW7DGTEl1u33Vi) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Find Gangnam Restaurant Reviews on Naver Place" task

The Naver Place Visitor & Blog Review Finder Actor will start running based on the input automatically. You can also change all the input fields, like place urls or ids, search keywords, and more, to match your specific use case.

### 3. Receive the "Find Gangnam Restaurant Reviews on Naver Place" 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 type, place, keyword, 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 "Find Gangnam Restaurant Reviews on Naver Place" task via API](https://apify.com/dataspryva/naver-place-visitor-and-blog-review-finder.md).

## FAQ

### What data can I get from Naver restaurant reviews for market research?

The Gangnam restaurant reviews task returns visitor reviews, linked blog posts, and place statistics. The dataset view includes review type, place name, search keyword, rating, review text, blog title, and blog date.

### How much does it cost to collect Gangnam restaurant reviews?

For the Gangnam restaurant reviews task, up to 100 results means a result charge of at most $0.099 on the Free plan. Actor start event charges and Apify platform compute usage are additional.

### Can I export Naver review data to CSV or Excel?

After running the Gangnam restaurant reviews task, download its dataset as CSV, Excel, JSON, XML, RSS, or an HTML table, or read it through the Apify API.

### How do I change the area or category for Naver restaurant reviews?

In the Gangnam restaurant reviews task, change the search phrase to the area or category you want, such as a different neighborhood or restaurant type. The current search phrase is 강남 맛집.

### Does collecting Naver restaurant reviews require a login or API key?

The Gangnam restaurant reviews task uses public, cookieless endpoints, so it requires no Naver login, cookie, or API key.

### Can I run Naver restaurant review research on a schedule or through an API?

The Gangnam restaurant reviews task can run on an Apify schedule, through the Apify API, or through integrations such as Zapier, Make, and n8n.

## About this Actor

This example demonstrates how to use [Naver Place Visitor & Blog Review Finder](https://apify.com/dataspryva/naver-place-visitor-and-blog-review-finder.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/dataspryva/naver-place-visitor-and-blog-review-finder.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/dataspryva/naver-place-visitor-and-blog-review-finder.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`).