Naver Place Scraper — Korean Local Business Leads 📍

More Fox Labs data actors: Fox Labs on Apify →

🎉 Pull Korean local businesses from Naver Place (네이버 플레이스) by keyword + region — name, phone, address, hours, coordinates, ratings and digital-booking flags — with no login and no API key. Built for local lead-gen & sales teams, franchise and site-selection analysts, and POS/SaaS vendors targeting Korean SMBs.

🔍 What is the Naver Place Scraper — and when should you use it?

In Korea, Naver Place is where local businesses live — the maps, reviews and booking layer that Korean customers actually use. This actor searches it for you: give it a Korean phrase like 강남 카페 (Gangnam cafes) or 부산 병원 (Busan hospitals) and it returns the top businesses for that query with their full public profile — name, category, phone, road address, business hours, coordinates, visitor/blog review counts and score, and whether the business uses Naver booking or N-Pay.

It reads Naver Place's own server-rendered page data, so there is no token to manage and no login — which keeps it robust when Naver changes its internals.

Use it when you need: a phone + address list for a business category in a district; competitor density, ratings and review counts by area; businesses that already use Naver booking / N-Pay (qualified POS/SaaS leads); or coordinates for mapping a local market.

Use something else when: you need every business in a huge city in one call. This actor returns the top results Naver Place shows for a query (about 50–60 per search); for wide coverage, run several district-level queries (강남 미용실, 서초 미용실, 송파 미용실 …) rather than one broad one.

🤖 Use with AI agents

Already on the Apify MCP server? Ask for this Actor by name: foxlabs/naver-place-scraper.

Your agent can pay for its own runs. This Actor is pay-per-event with agentic payments, so an agent can discover it, run it and settle the bill over x402 (USDC on Base) or Skyfire — no Apify account or API token of its own. Billing is the same either way: per delivered business, never for errors.

Otherwise paste this into Claude, ChatGPT, Cursor or any MCP-enabled assistant:

I want Korean local businesses from Naver Place using the Apify Actor
`foxlabs/naver-place-scraper`.

Input: `queries` is a list of Korean search phrases, each a region + category,
e.g. "강남 카페" (Gangnam cafes), "부산 병원" (Busan hospitals), "강남 미용실" (Gangnam hair salons).
Optional: `maxRecordsPerQuery` (default 100 — Naver shows ~50–60 top results per query),
`enrichDetail` (true/false — for sparse verticals like hair salons the phone is not in the list,
so fetch each detail page to recover it).
Each row has name, category, phone, address, businessHours, lat, lng, visitorReviewCount,
visitorReviewScore, hasBooking, hasNPay, bookingUrl, placeUrl.

Start with:
{ "queries": ["강남 카페"], "maxRecordsPerQuery": 100 }

Ask me which city/district and category I care about, run the Actor, then summarise the
businesses as a table with phone and rating.

Things you can ask your agent for:

• "List Gangnam cafes with their phone, rating and review count."
• "Which hospitals in Busan take Naver bookings?"
• "Pull hair salons across three Seoul districts and dedupe them into one sheet."

The machine-readable API, MCP config and OpenAPI definition live at apify.com/foxlabs/naver-place-scraper.md.

📋 Overview

Everything you need to turn Naver Place into a clean Korean local-business dataset — contact, location, ratings and booking signals — in one actor, with no login, cookies or API key.

Why teams pick this actor:

• 🔑 No login, no API key, no token — reads Naver Place's own server-rendered data.
• 📞 The fields a lead wants — phone, road address, hours, coordinates, ratings and review counts.
• 💳 Buying signals built in — hasBooking and hasNPay flag businesses already digitised (ideal POS/SaaS leads).
• 🌏 Any vertical, one input — cafes, hospitals, hair salons, dentists, gyms, hotels, pharmacies… just change the Korean phrase.
• 🧹 Clean, vertical-independent schema — same columns whatever you search; coordinates as numbers, no empty-promise fields.
• 💰 Pay only for results — per-business pricing; empty searches are never billed.
• 🤖 Agent-ready — MCP + x402 agentic payments.

✨ Features

• 🔍 Keyword + region search across Naver Place — no business IDs needed.
• 📇 Full public profile per business — name, category, phone, address, hours, coordinates, review count/score, booking flags, image, place URL.
• 📞 Phone enrichment (enrichDetail) — for verticals that hide the phone in the list (e.g. hair salons), fetch the detail page to recover it.
• 🗺️ Map-ready — latitude/longitude as numbers on every row.
• 🛡️ Robust by design — reads server-rendered page state (no fragile token replay); runs a real browser through rotating datacenter proxy.

🎬 Quick Start

curl -X POST "https://api.apify.com/v2/acts/foxlabs~naver-place-scraper/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json; charset=utf-8" \
  --data-binary '{"queries": ["강남 카페"], "maxRecordsPerQuery": 100}'

(Send the body as UTF-8 so the Korean query is preserved.)

🚀 Getting Started (3 steps)

1. Type your Korean queries — one per line, each a region + category (강남 카페, 부산 병원).
2. Set the size (optional) — maxRecordsPerQuery; turn on enrichDetail for sparse verticals like hair salons.
3. Run and export — get a clean dataset as JSON, CSV or Excel.

📥 Input

{
  "queries": ["강남 카페", "부산 병원"],
  "maxRecordsPerQuery": 100,
  "enrichDetail": false
}

Field	Type	Description
queries	array	Korean search phrases, one per line — each a region + category (강남 카페, 부산 병원, 강남 미용실).
maxRecordsPerQuery	integer	Caps businesses per query (default 100). Naver Place shows about 50–60 top results per query.
enrichDetail	boolean	For sparse verticals (e.g. hair salons) the phone is missing from the list; fetch each business's detail page to recover it. Adds one request per enriched business.
proxyConfiguration	object	Optional. Naver throttles raw and repeat requests, so the actor runs a real browser through Apify datacenter proxy with rotation by default.

📤 Output

One row per business, saved to the dataset.

Field	Type	Description
name	string	Business name
category	string	Naver category
phone	string	Phone (or Naver virtual number); for sparse verticals filled via enrichDetail
address	string	Road address
businessHours	object	Opening-hours status / description where Naver publishes it
lat / lng	number	Coordinates
visitorReviewCount / visitorReviewScore	number	Visitor review count and average score
blogCafeReviewCount / bookingReviewCount	number	Blog/cafe and booking review counts
hasBooking / hasNPay	boolean	Uses Naver booking / N-Pay
bookingUrl	string	Naver booking link where present
imageUrl	string	Representative photo
placeUrl	string	Naver Place page for the business
id	string	Naver Place ID

Every row also carries query; enriched rows carry phoneSource: "detail".

{
  "query": "강남 카페",
  "id": "1498100901",
  "name": "그라운드8",
  "category": "카페",
  "phone": "0507-1302-6392",
  "address": "도산대로49길 41 2층",
  "businessHours": { "status": "영업 중", "description": "01:00에 라스트오더" },
  "lat": 37.5257026,
  "lng": 127.0369307,
  "visitorReviewCount": 423,
  "visitorReviewScore": 4.97,
  "hasBooking": false,
  "hasNPay": true,
  "placeUrl": "https://m.place.naver.com/place/1498100901/home"
}

💼 Use cases

1. Local lead lists — phone + address for a category in a district. Input: queries: ["강남 미용실"], enrichDetail: true. Output: salons with phone and rating. Use: outbound sales calling lists.

2. POS / SaaS targeting — businesses already digitised with Naver booking or N-Pay. Input: queries: ["강남 카페", "홍대 카페"]. Output: rows flagged hasBooking / hasNPay. Use: prioritise accounts most likely to adopt payments/booking software.

3. Franchise & site selection — competitor density, ratings and review counts by area. Input: the same category across several districts. Output: one table with coordinates and ratings. Use: map saturation and pick sites.

4. Market research — category coverage and sentiment by region. Input: a category across target cities. Output: review counts/scores per business. Use: benchmark a local market.

🔗 Integration

JavaScript / Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('foxlabs/naver-place-scraper').call({
  queries: ['강남 카페'], maxRecordsPerQuery: 100,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);

Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')
run = client.actor('foxlabs/naver-place-scraper').call(
    run_input={'queries': ['강남 카페'], 'maxRecordsPerQuery': 100}
)
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

Written for apify-client 3 for Python, where call() returns a run object; with version 1 or 2 it returns a dict — write run['defaultDatasetId'] there.

Automation (n8n / Zapier / Make): schedule or webhook → HTTP request to the actor API with your queries → handle the JSON dataset → push to a sheet, CRM or dashboard.

📊 Pricing

Pay-per-event:

• $2.50 per 1,000 delivered businesses (place)
• $0.50 per 1,000 search queries (query)
• $1.00 per 1,000 phone enrichments (detail-enrich, only when enrichDetail is on)

Empty searches are never billed. View current pricing.

❓ FAQ

Do I need a Naver account, login or API key? No. The actor reads Naver Place's own public, server-rendered page data.

How many businesses do I get per query? Naver Place shows roughly 50–60 top results per query, and that is what a single query returns. For wider coverage, run several district-level queries rather than one broad one.

Why is the phone empty for some businesses? A few verticals (notably hair salons) don't show a phone in the list. Turn on enrichDetail and the actor fetches each business's detail page to recover it (business hours may still be unavailable for those verticals).

What language are the queries and data in? Queries and most fields are Korean. Send the input as UTF-8 so the Korean text is preserved.

Does it cover the whole country? Any region Naver Place indexes — write the region into the query (부산 병원, 제주 카페).

Can I export to CSV / Excel / JSON? Yes — directly from the Apify dataset.

What happens when a search finds nothing? The run succeeds with no rows for that query and you are not charged for it.

Is scraping this legal? It reads public business-profile data that Naver Place publishes for discovery. It contains business data, not personal user data. See below.

🐛 Troubleshooting

• The query came back as ?? ?? / zero results — the Korean text was not sent as UTF-8. Use a UTF-8 body (--data-binary, or the Apify console/UI which handles it).
• Phone missing for a vertical — turn on enrichDetail (hair salons and some verticals hide it in the list).
• Fewer rows than a city has — this is expected; Naver shows ~50–60 per query. Split into district-level queries.

⚠️ Trademark

Independent, third-party tool. Not affiliated with, endorsed by or connected to NAVER Corp. "Naver", "Naver Place" (네이버 플레이스) and related marks belong to their owners and are used here for identification only.

⚖️ Is it legal to scrape this data?

This actor reads only publicly published business-profile data (name, category, address, phone, hours, ratings) — not private or personal user data. Results can still contain personal data in edge cases (e.g. a person's name used as a business name); personal data is protected by Korea's PIPA, the GDPR and similar laws, so only process it with a legitimate basis. See Apify's blog post on the legality of web scraping.

🤝 Support & contact

• 🌐 Website: data.foxlabs.com.tr
• 📧 Email: info@foxlabs.com.tr
• 🐛 Issues: open a ticket in the Actor's Issues tab
• 🧰 More clean B2B data actors: Fox Labs on Apify

Changelog

0.1 — 2026-10-21

• Initial release: Korean local-business search on Naver Place by keyword + region. Returns name, category, phone, address, hours, coordinates, review counts/score, booking/N-Pay flags, booking URL, image and place URL. enrichDetail recovers the phone for sparse verticals. Reads server-rendered page state (no token); runs a browser through Apify datacenter proxy. Pay-per-event: delivered business + search query + phone enrichment.