How to Scrape Naver Map & Naver Place (2026): South Korea Business Leads, Menus & Visitor Reviews Guide ($0.50–$1.00/1K)

If you are building a B2B sales pipeline, retail store locator, F&B menu pricing intelligence platform, medical aesthetics directory (강남 피부과 / 성형외과), or consumer sentiment tracker in South Korea, relying on Google Maps will leave your dataset blind.

Due to South Korea's geospatial data export regulations, Google Maps has severely limited local POI coverage in Korea. Instead, Naver Map (map.naver.com) and Naver SmartPlace (m.place.naver.com) command over 75% of the South Korean local search market, serving more than 28 million monthly active users and indexing over 2.5 million active Korean businesses, restaurants, clinics, cafes, and retail stores.

However, engineering teams and market researchers quickly hit two major roadblocks when trying to extract Naver Place data at scale:

1. The Official Naver Open API 5-Item Cap: Naver's official Local Search API (openapi.naver.com/v1/search/local.json) restricts display to a maximum of 5 results per query (start=1), omits phone numbers (telephone was deprecated), and provides zero access to KRW menu prices, opening hours, social links, or visitor reviews.
2. Strict Anti-Bot & Dynamic Map Viewports: Scraping map.naver.com or m.place.naver.com directly with headless browsers triggers aggressive rate limits, Korean IP residential filtering, and heavy memory consumption ($15–$30+ per 1,000 places in proxy and compute overhead).

In this 2026 engineering guide, we break down how to extract complete South Korean business leads, KRW menu catalogs, WGS84 GPS coordinates, and receipt-verified visitor reviews (영수증 방문자 리뷰) using the UnitBytes Naver Place & Map Intelligence Suite on Apify—starting at $0.50 to $1.00 per 1,000 records with zero Korean accounts or API keys.

1. The 3 Specialized UnitBytes Naver Scrapers (2026 Comparison)#

Whether you need deep F&B menu catalogs, nationwide B2B lead lists across Seoul (서울), Busan (부산), Incheon (인천), and Jeju (제주), or tens of thousands of receipt-verified consumer reviews, UnitBytes provides three purpose-built cloud engines:

2. Official Naver Local Search API vs. UnitBytes Naver Suite#

Many international developers start by registering an application in the Naver Developers Console (developers.naver.com), only to discover that the official Local Search API was restricted to prevent commercial directory building:

3. Deep Dive: 5 High-ROI Workflows for South Korean Market Intelligence#

1. B2B Lead Generation & Merchant Acquisition (unitbytes/naver-map-scraper)

If you are selling POS systems, payment gateways, B2B SaaS, food-service distribution, medical supplies, or digital marketing services in South Korea, every local merchant's digital storefront lives on Naver SmartPlace.

Each record returned by Naver Map Scraper includes actionable merchant qualification signals:

• Contact Channels: phone (primary contact number), virtual_phone (Naver 0507 SmartCall tracking number—indicating an actively managed SmartPlace profile), local_phone (direct store landline), homepage_url, and sns_links (Instagram, Naver Blog, KakaoTalk Channel, Facebook, YouTube).
• Digital Commerce Adoption Flags: Filter prospects instantly by has_booking (uses Naver Booking / 네이버 예약), has_npay (accepts Naver Pay / 네이버페이), has_talktalk (active Naver TalkTalk chat widget / 네이버 톡톡), has_smart_order (table/pickup ordering / 스마트오더), and has_delivery (배달).
• Dual Korean Address & Subway Proximity: Full road_address (도로명주소), address (지번주소), postal_code, WGS84 latitude/longitude, and directions (e.g., "성수역 4번 출구에서 210m" / distance from nearest subway exit).

2. Restaurant, Cafe & Medical Clinic Menu Price Intelligence (unitbytes/naver-place-scraper)

In South Korea, not only restaurants and cafes (맛집 / 카페) publish full KRW price lists on Naver Place—dermatology clinics (피부과), dental offices (치과), hair salons (미용실), fitness studios (필라테스), and pet hospitals (동물병원) also list their exact treatment and service prices in the Naver Place Menu tab.

With includeMenus: true on Naver Place Scraper, you receive both a structured menus array and a human-readable menus_summary string for instant Excel/CSV analysis:

{
  "place_id": "1357924680",
  "name": "성수 로스터리 카페 (Seongsu Roastery Cafe)",
  "category": "카페,디저트",
  "road_address": "서울 성동구 연무장길 45 1층",
  "address": "서울 성동구 성수동2가 315-10",
  "phone": "0507-1400-0100",
  "latitude": 37.544512,
  "longitude": 127.056089,
  "rating": 4.68,
  "visitor_review_count": 1842,
  "blog_review_count": 695,
  "business_status": "영업 중",
  "business_hours_ detail": "매일 10:00 - 22:00 (라스트오더 21:30)",
  "has_booking": true,
  "has_npay": true,
  "has_smart_order": true,
  "menu_count": 14,
  "menus_summary": "시그니처 아인슈페너: 6,500원 | 핸드드립 에티오피아: 7,000원 | 소금빵: 3,800원",
  "menus": [
    {
      "name": "시그니처 아인슈페너",
      "price": "6,500원",
      "price_krw": 6500,
      "description": "직접 만든 수제 크림이 올라간 시그니처 메뉴",
      "is_recommended": true,
      "image_url": "https://ldb-phinf.pstatic.net/20260501_101/1714520000000_menu1.jpg"
    }
  ],
  "facilities": ["포장", "무선 인터넷", "반려동물 동반", "남/녀 화장실 구분", "주차"],
  "homepage_url": "https://instagram.com/seongsu_roastery_example"
}

3. Fraud-Proof Consumer Sentiment via Receipt-Verified Visitor Reviews (unitbytes/naver-place-reviews-scraper)

Unlike anonymous review platforms where competitors can post fake 1-star or 5-star reviews, Naver Place Visitor Reviews (영수증/결제 인증 방문자 리뷰) require proof of purchase—verified either by scanning a physical paper receipt (영수증), paying via Naver Pay (네이버페이), completing a Naver Booking (예약), or matching a corporate/personal credit card statement (결제내역).

Using Naver Place Reviews Scraper at just $0.50 per 1,000 reviews ($0.90/1K on Free tier), consumer brands and AI/NLP teams can extract:

• visit_verification_type: Exact verification badge (영수증 receipt OCR, 결제내역 card payment, 예약 booking, 주문 SmartOrder).
• Repeat Customer Loyalty (visit_count): Whether the review was written on the customer's 1st visit (1번째 방문) or 15th visit (15번째 방문), plus reviewer_total_reviews across all of Naver.
• Structured Sentiment Tags (visit_keywords): Naver's structured "What did you like?" voter tags ("음식이 맛있어요", "친절해요", "매장이 청결해요", "가성비가 좋아요").
• Merchant Engagement (owner_reply_text & owner_reply_date): Track how quickly and effectively store owners respond to customer feedback.

{
  "record_type": "review",
  "place_id": "1357924680",
  "place_name": "성수 로스터리 카페",
  "review_id": "6649f8a12b3c4d5e6f7a8b9c",
  "rating": 5.0,
  "review_text": "아인슈페너 크림이 정말 쫀쫀하고 소금빵도 갓 구워져 나와서 너무 맛있었어요! 직원분들도 친절하십니다.",
  "visit_date": "2026-10-28",
  "created_at": "2026-10-29T04:15:22Z",
  "visit_count": 3,
  "visit_verification_type": "영수증",
  "visit_keywords": ["커피가 맛있어요", "디저트가 맛있어요", "친절해요", "인테리어가 멋져요"],
  "author_nickname": "맛집탐험가99",
  "reviewer_total_reviews": 148,
  "photo_count": 2,
  "owner_reply_text": "3번째 재방문 진심으로 감사드립니다! 언제나 신선한 원두로 보답하겠습니다 :)",
  "place_url": "https://m.place.naver.com/place/1357924680/review/visitor"
}

4. Quickstart: Scrape Naver Map & Place in Python, Node.js & cURL#

You can trigger any of the three UnitBytes Naver Actors via the Apify Console UI (zero coding required) or integrate them directly into your data pipeline using the official Apify SDK.

Python Example (apify-client)

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")

# 1. Extract Korean Business Profiles + KRW Menus + Embedded Visitor Reviews
run_input = {
    "searchQueries": ["성수동 카페", "강남 피부과"],
    "maxPlacesPerQuery": 50,
    "includeMenus": True,
    "maxReviews": 10,
    "reviewsSort": "recent",  # "recommended" or "recent"
}

run = client.actor("unitbytes/naver-place-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"[{item['place_id']}] {item['name']} ({item['category']})")
    print(f"  Road Address: {item['road_address']} | Phone: {item['phone']}")
    print(f"  Reviews: {item['visitor_review_count']} visitor / {item['blog_review_count']} blog")
    print(f"  Top Menus: {item['menus_summary']}")

Dedicated Bulk Visitor Reviews Extraction (unitbytes/naver-place-reviews-scraper)

# 2. Extract 500 Receipt-Verified Visitor Reviews per Place ($0.50/1K)
reviews_run = client.actor("unitbytes/naver-place-reviews-scraper").call(
    run_input={
        "placeUrls": [
            "https://m.place.naver.com/restaurant/1357924680/home",
            "https://map.naver.com/p/entry/place/1357924680",
        ],
        "maxReviews": 500,
        "reviewsSort": "recent",
    }
)

for review in client.dataset(reviews_run["defaultDatasetId"]).iterate_items():
    print(f"{review['visit_date']} ({review['visit_verification_type']} #{review['visit_count']}): {review['review_text'][:80]}...")

REST API / cURL Example

curl -X POST "https://api.apify.com/v2/acts/unitbytes~naver-map-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "searchQueries": ["홍대 맛집", "부산 해운대 카페"],
    "maxPlacesPerQuery": 50
  }'

5. Pro Tips for High-Yield South Korea Regional Scraping (시/군/구/동 Grid Strategy)#

When building a comprehensive nationwide or city-wide directory in South Korea, broad top-level queries like "서울 카페" (Seoul Cafes) only surface the top ~200–300 most popular places ranked by Naver's relevance algorithm.

To achieve 99%+ market coverage across Seoul or all of South Korea, partition your searchQueries by Administrative District (구 / Gu) or Neighborhood (동 / Dong) + Subway Station (역 / Station):

• Seoul High-Density Commercial Districts:
• "강남역 피부과", "신사동 가로수길 피부과", "청담동 피부과", "압구정로데오 피부과"
• "성수동1가 카페", "성수동2가 카페", "연남동 카페", "한남동 카페", "을지로 카페"
• Automatic Cross-Query Deduplication: All UnitBytes Naver scrapers automatically deduplicate place_id across overlapping searchQueries and placeUrls within the same run—so you never pay twice for a business that appears in both "성수동 카페" and "성수역 카페".

Frequently Asked Questions (FAQ)