Naver Place Reviews Scraper (네이버 플레이스 리뷰 수집기)

Naver Place Reviews Scraper extracts visitor reviews from Naver Place and Naver Map (네이버 지도), the review platform that dominates Korea the way Google Maps does elsewhere. Type a search keyword such as 강남 카페 or 부산 치과, or paste a Naver Place ID, and get every review as clean JSON, CSV or Excel: rating, review text, date, author nickname and visit count, plus the place name, category and address.

No Naver login. No API key. No headless browser. Pay only for the reviews you receive.

What does Naver Place Reviews Scraper do?

Naver has no public reviews API. This Naver review scraper reads the same server-rendered place list and review feed that the Naver Map website uses, so it works for every business type listed on Naver Place:

• Restaurants, cafes, bars and bakeries (맛집, 카페)
• Hospitals, dental clinics, dermatology and plastic surgery clinics (병원, 치과, 피부과)
• Hair salons, nail shops, spas and gyms (미용실, 네일, 헬스장)
• Hotels, pensions, guesthouses (호텔, 펜션)
• Academies, kids cafes, pet shops, car repair, real estate agents

One run can cover a whole district: search 홍대 맛집, take the first 20 places, pull 100 reviews from each, and you have 2,000 structured Korean reviews in a couple of minutes.

Why use this Naver review scraper?

• Works where others fail. The Naver Map JSON search API is captcha-gated and causes the frequent failed runs you see on other Naver scrapers. This Actor uses the server-rendered place list and the public review endpoint instead, so runs do not die on captcha.
• Pure HTTP, no browser. Fast, cheap on compute, and a single run handles thousands of reviews.
• Pay per review. $1.00 per 1,000 reviews, billed only for results actually returned. No subscription, no minimum.
• Keyword or ID input. Search by district and category, or monitor specific places by ID.
• Ready for AI agents. Every Apify Actor is also an API endpoint and an MCP server, so Claude, ChatGPT, LangChain or n8n workflows can call Naver Place Reviews Scraper directly.

Output: what data can you extract from Naver Place reviews?

Each dataset item is one review joined with its place:

Field	Example	Description
placeId	2093423408	Naver Place business ID
placeName	CAFE 00:00	Business name
placeCategory	카페,디저트	Naver category
placeAddress	서울 강남구 학동로46길 27 1층	Road address
reviewId	6a9942f104c5b9f89193ebaa	Unique review ID (use it to deduplicate between runs)
rating	5	Star rating, 1 to 5, null when the reviewer skipped it
body	인테리어 너무 감각적이고 디저트들도 너무 예쁘고 맛있어요!	Full review text in Korean
created	9.3.목	Review date as shown on Naver (month.day.weekday)
visitCount	1	How many times the reviewer has visited
authorNickname	짱아아아아아	Public nickname
placeUrl	https://m.place.naver.com/place/2093423408/review/visitor	Link to the review page

Example output (JSON):

{
  "placeId": "2093423408",
  "placeName": "CAFE 00:00",
  "placeCategory": "카페,디저트",
  "placeAddress": "서울 강남구 학동로46길 27 1층",
  "reviewId": "6a9942f104c5b9f89193ebaa",
  "rating": 5,
  "body": "인테리어 너무 감각적이고 디저트들도 너무 예쁘고 맛있어요! 매장 분위기도 좋고 직원 분들도 친절하셔서 3시간이나 있다가 갑니다 ☺️",
  "created": "9.3.목",
  "visitCount": 1,
  "authorNickname": "짱아아아아아",
  "placeUrl": "https://m.place.naver.com/place/2093423408/review/visitor"
}

Download the dataset as JSON, CSV, Excel, XML or RSS from the Apify Console, or fetch it through the API.

How to scrape Naver Place reviews

1. Open Naver Place Reviews Scraper in Apify Store and click Try for free.
2. Enter one or more keywords (강남 카페, 제주 흑돼지, 분당 피부과) or paste place IDs.
3. Set Max reviews per place (default 50) and Max places per keyword (default 10).
4. Click Start. Results appear in the Output tab within a minute or two.
5. Export, or schedule the run to repeat daily for review monitoring.

Where do I find a Naver Place ID?

Open any business on Naver Map and look at the URL. The number after /place/, /restaurant/, /hospital/ and similar paths is the place ID:

https://m.place.naver.com/restaurant/2093423408/home   →  placeId = 2093423408
https://map.naver.com/p/entry/place/1670148621          →  placeId = 1670148621

Input parameters

Parameter	Type	Default	Description
keywords	array	["강남 카페"]	Naver Map search queries. Each keyword yields up to maxPlacesPerKeyword places from the first result page.
placeIds	array	[]	Naver Place IDs to scrape directly. Combined with keyword results and deduplicated.
maxPlacesPerKeyword	integer	10	Places taken per keyword (1 to 100).
maxReviewsPerPlace	integer	50	Reviews collected per place (1 to 5000). Newest first.
proxyConfiguration	object	Apify residential, KR	Naver rate-limits datacenter IPs. Keep the Korean residential proxy unless you run from Korea.

Example input:

{
  "keywords": ["강남 카페", "홍대 맛집"],
  "placeIds": ["2093423408"],
  "maxPlacesPerKeyword": 10,
  "maxReviewsPerPlace": 100,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "KR" }
}

How much does it cost to scrape Naver reviews?

Naver Place Reviews Scraper uses Apify's pay-per-event pricing: $0.001 per review ($1.00 per 1,000 reviews). You are charged only for reviews that land in your dataset. A run that returns nothing costs nothing beyond Apify platform usage.

Reviews	Price
1,000	$1.00
10,000	$10.00
100,000	$100.00

Apify's free plan includes $5 of monthly usage, enough for several thousand reviews to evaluate the Actor. Residential proxy traffic is billed by Apify separately at the platform rate; the Actor downloads only small HTML and JSON payloads, so proxy cost per review is a fraction of a cent.

Use cases for Naver Place review data

• Review monitoring (리뷰 모니터링): Schedule a daily run for your own stores or franchise branches and push new reviews to Slack, email or a Google Sheet.
• Local SEO and 플레이스 마케팅 agencies: Track client sentiment and competitor reviews across a district.
• Market research and site selection: Compare how customers talk about cafes in 성수 versus 연남 before opening a new location.
• Korean NLP and LLM training data: Thousands of authentic, informal Korean reviews with ratings for sentiment analysis, aspect extraction or fine-tuning.
• Hospitality and medical tourism: Analyze reviews of hotels, clinics and dermatology centers that overseas visitors search for on Naver.
• AI agents: Let an agent answer "what do people say about this restaurant?" by calling the Actor through MCP.

Use Naver Place Reviews Scraper from code

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("romantic_boysenberry/naver-place-reviews-scraper").call(run_input={
    "keywords": ["강남 카페"],
    "maxPlacesPerKeyword": 5,
    "maxReviewsPerPlace": 100,
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["placeName"], item["rating"], item["body"][:60])

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_API_TOKEN>' });
const run = await client.actor('romantic_boysenberry/naver-place-reviews-scraper').call({
  keywords: ['홍대 맛집'],
  maxReviewsPerPlace: 50,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, 'reviews');

cURL

curl -X POST "https://api.apify.com/v2/acts/romantic_boysenberry~naver-place-reviews-scraper/run-sync-get-dataset-items?token=<YOUR_API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"keywords":["부산 치과"],"maxPlacesPerKeyword":5,"maxReviewsPerPlace":30}'

The Actor also works as an MCP server for Claude Desktop, Cursor and other agents, and plugs into n8n, Make, Zapier and LangChain through the standard Apify integrations.

Tips for best results

• Korean keywords return far better place matches than English ones. Use 강남 카페, not Gangnam cafe.
• Combine a district and a category (판교 헬스장, 광안리 횟집) to keep the first result page relevant.
• To monitor the same businesses over time, pass placeIds and deduplicate on reviewId.
• Reviews are returned newest first. Set maxReviewsPerPlace to a small number for cheap daily deltas.
• Keep the Korean residential proxy on. Naver answers datacenter IPs with a captcha page.

Limitations

• Only reviews visible to anonymous visitors are collected. Reviews hidden by the business or by Naver are not available.
• Keyword search reads the first page of results, roughly 20 to 50 places per keyword. Use several narrower keywords to cover a large area.
• The created field is the display string Naver shows (9.3.목); Naver does not expose a full timestamp to anonymous visitors.
• Naver changes its markup occasionally. If a run suddenly returns zero places, the Actor fails loudly instead of silently succeeding; check the run log and open an issue.

Legal and ethical use

Naver Place Reviews Scraper collects only publicly visible review content and the public nickname shown on the review. It does not log in, does not bypass access controls and does not collect private contact details. Review text may be protected by copyright and personal data rules in your jurisdiction; use the data for analysis, research and monitoring in line with Naver's terms and applicable law, including Korea's Personal Information Protection Act. You are responsible for how you use the output.

FAQ

Does Naver have an official reviews API? No. The Naver Developers API covers local search (name, address, category) but not visitor reviews. This Actor fills that gap.

Can it scrape Naver blog reviews or photos? This Actor focuses on visitor reviews (방문자 리뷰). Blog reviews and photo feeds are planned as separate Actors.

Why do I get zero places from a datacenter proxy? Naver serves a captcha to most datacenter IP ranges. Use the default Korean residential proxy group.

How fresh is the data? Every run fetches live from Naver. Nothing is cached.

Can I run it on a schedule? Yes. Use Apify Schedules to run hourly, daily or weekly, and connect a webhook or integration to receive new reviews automatically.

Is there a free trial? Apify's free plan gives you $5 of usage every month, so you can test Naver Place Reviews Scraper without a credit card.

Related Naver and Korean data Actors

• Naver Map Search Results Scraper for place details without reviews
• Naver Blog & Cafe Scraper for blog posts and cafe threads
• Coupang Scraper for Korean e-commerce product data
• More Korean Actors from this developer are on the way: Naver Place search, Naver Blog search and Olive Young reviews.

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네이버 플레이스 리뷰 수집기 (한국어 안내)

네이버 플레이스 리뷰 수집기는 네이버 지도·네이버 플레이스의 방문자 리뷰를 키워드 또는 플레이스 ID로 수집해 JSON, CSV, Excel로 내려받는 Apify 액터입니다.

• 로그인, API 키, 브라우저 설치 모두 불필요
• 리뷰 1건당 $0.001 (1,000건에 $1), 받은 만큼만 과금
• 맛집·카페·병원·치과·피부과·미용실·호텔·학원 등 네이버 플레이스의 모든 업종
• 출력 필드: 플레이스 ID, 상호, 업종, 주소, 리뷰 ID, 별점, 리뷰 본문, 작성일, 방문 횟수, 작성자 닉네임, 리뷰 URL
• 활용: 매장·가맹점 리뷰 모니터링, 플레이스 마케팅 대행사 리포트, 상권 분석, 경쟁사 리뷰 분석, 한국어 감성 분석 데이터셋
• 네이버 지도 검색 API의 캡차 차단을 우회하지 않고, 서버 렌더링 페이지와 공개 리뷰 피드만 사용하므로 실행 실패가 적습니다
• 공개된 리뷰와 공개 닉네임만 수집하며 개인정보는 수집하지 않습니다. 수집 데이터는 관련 법령과 네이버 약관을 지켜 사용하세요

사용법: 액터 페이지에서 Try for free → 검색어(예: 강남 카페) 입력 → Start → Output 탭에서 다운로드. 예약 실행(Schedules)으로 매일 자동 수집도 가능합니다.