Naver Map Scraper - Places, Reviews, Menus, Photos & Phones

What does Naver Map Scraper do?

Naver Map Scraper extracts places from Naver Map (네이버 지도 / Naver Place), Korea's main local search, and turns search keywords, map areas or place links into structured rows: name, category, address, phone, coordinates, opening hours, menu with prices, website and Instagram, rating, review and save counts, plus each place's visitor reviews, blog reviews and photos. Built for lead generation, local market research, restaurant and retail intelligence and review monitoring in Korea.

Naver Map Scraper - Naver Place scraper - Naver Map API alternative - 네이버 지도 크롤러 - Korean business leads

• Four kinds of rows in one actor: places, visitor reviews, blog / cafe reviews and photos. The recordType field says which.
• Past Naver's 300-per-keyword limit: give a point and a radius (or a box) and the area is split into cells until every matching place is collected - 1,000 cafés around Hongdae in 112 seconds in our test run.
• Place details as a cheap add-on: hours by day with break times and last order, the full menu with prices, homepage, Instagram and blog links, amenities, parking, payment methods, subway exit and walking time, review statistics, voted keywords, Michelin and TV appearances.
• Naver's own filters: open now, 24 hours, delivery, takeout, reservations, Naver Pay, coupons, newly opened, wheelchair access, Michelin, menu keyword, place type.
• Monitoring mode: schedule it and get only new or changed places, and only reviews you have not received before.
• No login, cookies or Naver API key: the actor reads the same public data Naver Map shows a signed-out visitor.
• Pay per row, no start fee: $0.40 per 1,000 places, $0.72 per 1,000 for the details, $0.35 per 1,000 reviews.

What data can you get from Naver Map?

🏷️ Name, category, place type	📍 Road and lot address, coordinates	📞 Phone and 0507 virtual number
⭐ Rating, visitor and blog review counts	🔖 Save count (how many users saved it)	🕒 Open now, hours by day, breaks, last order
🍽️ Menu with prices and photos	🌐 Homepage, Instagram, blog, TalkTalk	📅 Naver Booking link, Naver Pay, delivery
🚇 Nearest subway exit, walk time, bus stops	🅿️ Parking, facilities, payment methods	📊 Review themes, voted keywords, star bands
💬 Visitor reviews with owner replies	📝 Blog and cafe posts (내돈내산 flag)	📷 Owner and visitor photos, clips

How to scrape Naver Map with Naver Map Scraper

1. Open the actor and click Try for free.
2. Type one or more search keywords the way you would on Naver Map, e.g. 강남 맛집, 홍대 카페, 서초구 치과, or paste place links.
3. Optional: set search coordinates and a radius to sweep a whole area, switch on Naver's filters, reviews, blog reviews or photos.
4. Click Start and download the rows as JSON, CSV or Excel, or read them through the API.

⬇️ Input

Field	What it does
searchKeywords	Keywords, e.g. 강남 맛집. Korean gives the richest results; English works too.
urls	Place links (map.naver.com/p/entry/place/<id>, m.place.naver.com/<type>/<id>, pcmap.place.naver.com/...), naver.me short links, bare place ids, or a Naver Map search link (runs as a keyword).
maxResultsPerKeyword	Places per keyword or per area sweep (default 100; Naver serves 300 per keyword).
maxItems	Cap on places for the whole run.
searchCoordinates	"latitude,longitude". Ranks around the point and adds each place's distance.
searchRadiusKm / boundingBox	Sweep every matching place in a circle (max 20 km) or a box, past the 300 limit.
sortBy	Relevance, nearest, most reviewed, most saved.
businessType	Restaurants, cafes, hospitals, hair salons, beauty, hotels, attractions, pharmacies, pet services.
openNow, open24h, delivery, takeout, acceptsReservations, naverPay, hasCoupon, newlyOpened, wheelchairAccessible, michelinOnly, menuKeyword	Naver's own filters, applied by Naver.
extraFilters	Any other Naver list filter as JSON, e.g. {"department": "피부과"} for clinics.
includeDetails	The place-details block (default on).
includeEnglish	nameEn, categoryEn, addressEn from Naver's own English version.
includeReviews, maxReviewsPerPlace, reviewSort, reviewsSince, onlyNewReviews	Visitor reviews per place.
includeBlogReviews, maxBlogReviewsPerPlace, onlyOwnMoneyBlogReviews	Blog / cafe posts per place.
includePhotos, maxPhotosPerPlace, photoSource	Photos per place: all, owner, visitor-review or clips.
withPhoneOnly, withWebsiteOnly, minRating, minReviews, addressContains, categoryContains	Filters checked before anything is charged.
monitoringMode, emitUnchanged, monitoringStateKey	Return only new or changed places on scheduled runs.
proxyConfiguration, maxConcurrency	Optional. Naver answers without a proxy.

Input JSON

{
    "searchKeywords": ["강남 맛집", "홍대 카페"],
    "maxResultsPerKeyword": 100,
    "includeDetails": true,
    "includeReviews": true,
    "maxReviewsPerPlace": 20
}

Every café within 1 km of Hongdae (area sweep)

{
    "searchKeywords": ["카페"],
    "searchCoordinates": "37.5567,126.9227",
    "searchRadiusKm": 1,
    "maxResultsPerKeyword": 3000
}

Clinics with a phone, open now, in one district

{
    "searchKeywords": ["역삼동 피부과"],
    "openNow": true,
    "withPhoneOnly": true,
    "addressContains": ["역삼동"]
}

Naver pads a district search with places from neighbouring areas (on 2026-10-28, 역삼동 피부과 served 300 places, 130 of them in 역삼동; 율현동 치과 served 40, 2 in 율현동). addressContains drops the rest before the charge.

⬆️ Output

Each row has a recordType. The Output tab has views for places, contacts, place details, visitor reviews, blog reviews and photos.

Place (from the 홍대 카페 run, details on, trimmed):

{
  "recordType": "place",
  "place_id": "1503644539",
  "name": "아벨롭 홍대본점",
  "nameEn": "Avelop",
  "category": "카페,디저트",
  "address": "서울 마포구 서교동 375-2",
  "roadAddress": "서울 마포구 양화로15안길 6 Avelop",
  "phone": "02-336-8897",
  "primaryPhone": "02-336-8897",
  "latitude": 37.5544506,
  "longitude": 126.9188258,
  "visitorReviewsTotal": 4243,
  "visitorReviewsScore": 4.95,
  "blogReviewsTotal": 4310,
  "saveCount": "126,000+",
  "saveCountNum": 126000,
  "businessStatus": "영업 중",
  "instagram": "https://www.instagram.com/avelop_official?igsh=MWc3enU5dGVja3l6MA==",
  "menus": [{ "name": "아벨롭 라떼", "price": "7000", "priceText": "7,000원", "recommend": true }],
  "subwayStations": [{ "stationName": "홍대입구역", "typeDesc": "홍대입구역 경의중앙선", "nearestExit": "1", "walkTime": 8, "walkingDistance": 468 }],
  "votedKeywords": [{ "code": "coffee_good", "name": "커피가 맛있어요", "count": 2841 }],
  "placeUrl": "https://map.naver.com/p/entry/place/1503644539",
  "searchKeyword": "홍대 카페",
  "searchRank": 7,
  "hasDetails": true
}

Visitor review:

{
  "recordType": "review",
  "place_id": "1789177874",
  "placeName": "신이도가",
  "reviewId": "6ae080e4c53f858b2aab22ad",
  "rating": 5,
  "body": "음료가 맛있어용!!",
  "authorNickname": "damnew",
  "authorReviewCount": 69,
  "visitedDate": "2026-10-27",
  "createdDate": "2026-10-27",
  "votedKeywords": ["커피가 맛있어요", "음료가 맛있어요"],
  "visitTags": ["예약 없이 이용", "바로 입장", "친목", "친구"],
  "verification": "영수증",
  "receiptVerified": true,
  "ownerReply": { "body": "안녕하세요, 홍대 카페 신이도가(한옥카페) 입니다. 소중한 의견 남겨주셔서 감사합니다...", "date": "2026-10-28" }
}

Blog review rows carry title, contents (the excerpt Naver shows), url, authorName, sourceType (blog or cafe), publishedDate and ownMoney (Naver's 내돈내산 flag). Photo rows carry photoUrl (full size), source (business, visitorReview, clip), mediaType, authorNickname, date and the review it belongs to.

Fields

Measured on our test runs (1,200 places, 4,000 reviews, 1,000 blog reviews, 1,000 photos, 2026-10-28):

Field	Filled	Field	Filled
name, category, address, roadAddress, coordinates	100%	primaryPhone (own or 0507 number)	82%
visitorReviewsTotal	96%	saveCount	100%
businessStatus (open now)	93%	conveniences	82%
businessHours (details)	93%	menus (details)	87%
homepage (details)	73%	instagram (details)	64%
description (details)	86%	subwayStations (details)	99%
reviewStats (details)	96%	votedKeywords (details)	95%
review body	97%	review rating	98%
review photos	84%	owner reply	20%
blog title, url, date	100%	photo URL	100%

visitorReviewsScore appears only where Naver shows a star rating (28% of places in those runs); the phone is withheld by some owners (hasMobilePhoneNumber says when a number exists but is hidden). Search-only fields (saveCount, hasNPay, distance, searchRank) are empty on rows built from a place link, because Naver shows them on its search list.

Use cases

• 📇 Lead generation: restaurants, clinics, salons or shops in a district with phone, website and Instagram, filtered to those with a phone or website.
• 🗺️ Local market research: every café or clinic in an area with ratings, review and save counts, price signals and opening hours.
• 🍜 Restaurant and F&B intelligence: menus with prices, best-selling dishes, average spend, review themes and keywords across competitors.
• ⭐ Review monitoring: new visitor reviews and owner replies for your branches or competitors on a schedule.
• 📝 Influencer and content research: blog and cafe posts about a place, with the 내돈내산 (self-paid) flag.
• 🧭 Location data for apps: coordinates, transit access, parking and facilities for Korean points of interest.

How much does it cost to scrape Naver Map?

Pay per row, no start fee. Places removed by your filters, duplicates and unchanged places in monitoring mode are not charged.

Event	Price per 1,000
Place	$0.40
Place details (add-on on a place row)	$0.72
Visitor review	$0.35
Blog review	$0.40
Photo	$0.18

Example run (our test runs)	Rows	Cost
20 places with details	20	$0.022
1,000 cafés with details (area sweep)	1,000	$1.12
200 places + 20 reviews, 5 blog reviews, 5 photos each	6,200	$2.20
1,000 places without details	1,000	$0.40

Set Maximum cost per run in the run options to cap any run; the actor stops cleanly at the limit.

Run it on a schedule

Turn on monitoringMode (and onlyNewReviews for reviews), save the input as a task and schedule it daily or weekly. The first run returns everything and remembers it; later runs return only places that are new or changed (with changeType and changedFields; DETAILS = a place an earlier run delivered without place details, delivered again with them because this run reads them) and only reviews that were not returned before. In our test, the second run of a 50-place watch list returned 0 rows, charged nothing and cost $0.0004 in platform usage.

Integrations, API & MCP

• Schedules and webhooks: run on a schedule and get a call when a run finishes.
• Make, Zapier, n8n, Google Sheets, Slack: connect through Apify's integrations.
• API: start runs and read results from Python or JavaScript with the Apify client.
• MCP: AI agents can call the actor through the Apify MCP server.

More scrapers from TopApi

• 🛒 Naver Shopping Scraper: Naver Plus Store products, prices, sellers and reviews
• 🍎 Apple Maps Scraper: places, phones, hours and ratings from Apple Maps
• 🗺️ Yandex Maps Scraper: businesses and reviews from Yandex Maps
• ⭐ Google Maps Reviews Scraper: reviews from Google Maps places

All TopApi actors: apify.com/TopApi

Limits & empty runs

• Naver serves at most 300 places per keyword; for more, use an area sweep (searchCoordinates + searchRadiusKm, or boundingBox) or split the keyword by district.
• Naver shows about 100 blog / cafe posts per place; visitor reviews have no cap (50 per page).
• Some filters exist only for some place types: delivery and takeout for restaurants and cafes; the run summary says when one was not applied.
• Most saved and most reviewed sorting apply to restaurants and cafes.
• A run that finds nothing ends with a message saying why (no match, filters, nothing new in monitoring mode) and charges nothing. A run Naver refuses completely ends as failed and charges nothing.

❓ FAQ

How much does Naver Map Scraper cost?

$0.40 per 1,000 places, plus $0.72 per 1,000 places for the details block, $0.35 per 1,000 reviews, $0.40 per 1,000 blog reviews and $0.18 per 1,000 photos. No start fee.

How many places can Naver Map Scraper return?

300 per keyword, Naver's own limit. An area sweep collects every matching place inside a radius or box; our 1 km Hongdae sweep returned 1,000 cafés.

Can I get phone numbers and websites of Korean businesses?

Yes. phone is the business's own number, virtualPhone Naver's 0507 smart-call number, and primaryPhone gives one column. Homepage, Instagram and blog links come with the details.

Can Naver Map Scraper collect reviews?

Yes: visitor reviews (text, rating, dates, keywords, visit tags, photos, owner reply, receipt check) and blog / cafe posts, each as their own rows.

Can I monitor new reviews or new places on a schedule?

Yes. monitoringMode returns only new or changed places; onlyNewReviews returns only reviews not returned before.

Does it give English names and addresses?

Yes, with includeEnglish: Naver's own English name, category and address next to the Korean fields, at no extra charge.

Can I use Naver Map Scraper with the Apify API or Python?

Yes, through the API tab with the Apify client for Python or JavaScript.

Can AI agents use Naver Map Scraper through MCP?

Yes, through the Apify MCP server.

Do I need a Naver account, login or API key?

No.

Why did my run return no results?

The status message says why: no match for the keyword, your filters removed every place, or nothing changed since the last monitoring run. Korean keywords with a place name or district (강남 맛집) work best.

Your feedback

Missing a field or a filter? Open an issue on the Issues tab and we will look at it.