Naver Real Estate Scraper - Korea Property Listings 🚀

🎉 Every Naver Real Estate listing, in Korean, with the owner-verification badge already read

For analysts pricing the Korean market, agencies sourcing stock, and anyone tired of scrolling the app by hand

🔎 What is the Naver Real Estate Scraper - Korea Property Listings — and when should you use it?

The Naver Real Estate Scraper - Korea Property Listings turns Naver Real Estate (부동산) listings for any Korean region — sale, jeonse and monthly rent into clean, structured rows you can filter, export and feed straight into a spreadsheet, database or AI agent. No account, no portal API key, no browser automation to maintain.

Use it when you need: Korean property rows from Naver Real Estate (land.naver.com), Korea's listing inventory of record: asking prices for sale (매매), jeonse deposits (전세), monthly rents (월세) and short-term lets. Each row carries the complex, floor, exclusive and supply area, build year, facing, brokerage, owner-verification badge, management fee and coordinates. Korea's 16 cities and provinces and all 256 districts resolve by Korean name; neighbourhoods by name or Naver region code.

Use something else when: the property data you need is not on Naver Real Estate. Use Batdongsan Scraper for Vietnam's property portal — the same listing shape for a next-door market. Use 99acres Scraper for India property listings, sale and rent across every Indian city. Use Zameen Scraper for Pakistan's biggest portal — listings, prices and dealer contacts. This actor covers the listings Naver Real Estate's own feed serves: live asking prices, deposits and rents with their complex, floor plan and brokerage context. Full advert photo sets and each complex's statistics pages are separate surfaces and out of scope; sold-price (실거래가) history is a different Naver dataset and not part of the feed rows.

🤖 Use with AI agents

Already connected to the Apify MCP server? Just ask for this Actor by name: sian.agency/naver-property-scraper

Your agent can pay for its own runs. This Actor is eligible for agentic payments, so an agent can discover it, run it and settle the bill over x402 (USDC on Base) or Skyfire — without an Apify account or API token of its own. Billing is the same either way: per successful row, never for errors.

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

I want Naver Real Estate property listings and prices for any Korean region using the Apify Actor `sian.agency/naver-property-scraper`.

Use it when I need: Korean property rows from Naver Real Estate (land.naver.com), Korea's listing inventory of record: asking prices for sale (매매), jeonse deposits (전세), monthly rents (월세) and short-term lets. Each row carries the complex, floor, exclusive and supply area, build year, facing, brokerage, owner-verification badge, management fee and coordinates. Korea's 16 cities and provinces and all 256 districts resolve by Korean name; neighbourhoods by name or Naver region code.

Don't use it when: the property data you need is not on Naver Real Estate — use batdongsan-property-scraper or 99acres-property-scraper or zameen-property-scraper instead.

How to call it: give `locations` a list of Korean region names (강남구, 송파구, 수원시장안구) or Naver's 10-digit region codes; pick `dealType` (sale, jeonse, monthly or shortterm); narrow with `propertyTypes` (A01 = 아파트 apartments, A02 = 오피스텔 officetels and 23 more — leave empty for every type); set price or area bounds and `maxResults`; set `includeDetails` for the full record of each listing.

Start with this input:
{
  "operation": "search",
  "locations": [
    "강남구",
    "연수구"
  ],
  "dealType": "sale",
  "propertyTypes": [
    "A01"
  ],
  "maxResults": 100
}

Ask me which Korean regions to cover, which side of the market (sale, jeonse, monthly rent or short-term), which property types, and how many listings the run should stop at, then run the Actor and summarise the results as a table.

Things you can ask your agent for:

• Pull every sale listing in 강남구 with price, exclusive area, floor and brokerage.
• List jeonse apartments in 송파구 between 5억 and 9억, newest first, with the owner-verification badge.
• Show every monthly-rent one-room (C01) in 서대문구 under 보증금 2천만 with the monthly rent and management fee.

Machine-readable API, MCP config and OpenAPI definition for this Actor are published at apify.com/sian.agency/naver-property-scraper.md.

📋 Overview

Naver Real Estate (네이버 부동산) is where Korea's property market actually happens. Korean industry commentary puts its share of verified listings around 90%, and almost every Korean property app cross-checks against it. This actor reads the feed the site's own web app loads and hands you the rows.

Why professionals choose us:

• ✅ Built against the live feed: the two rival actors on the Store target the map surface Naver retired in 2026; this one speaks to what the site loads today
• 🏆 The inventory of record: around 90% of Korea's verified listings, 14,700+ active sale listings in 강남구 alone
• 🪪 The owner-verification badge: Naver confirms which posters own the home (집주인 매물): the direct-deal shortlist, read off the listing itself
• 🏦 All four deal types in one actor: 매매 sale, 전세 jeonse, 월세 monthly rent, 단기임대 short-term, all in one place
• 🔁 Brokerage competition on every row: how many brokerages hold the same unit, straight from the feed
• 🇰🇷 Regions that match how Koreans search: 16 cities and provinces and all 256 districts by name, neighbourhoods by name or code

✨ Features

• 🔍 Two operations in one actor: search any Korean region's live listings, or expand specific listing numbers to their full record
• 🗺️ Every region Naver indexes: 16 cities and provinces, 256 districts by Korean name, neighbourhoods by name or Naver's own region code
• 🏠 All 25 property types: apartments, officetels, villas and row houses, one-rooms, shops, offices, buildings, land, factories, knowledge-industry centers and more
• 🤝 One deal type per run, your choice: sale, jeonse, monthly rent or short-term, so the price column always means one thing
• 🪜 The fields a Korean buyer screens on: exclusive and supply area, floor of total, facing, build year, management fee
• 🪪 Owner-verified filter: keep only the listings Naver itself has confirmed as owner-posted
• 📄 Full record as an add-on: feature text, room and bath counts, parking totals, moving-in terms and exact coordinates
• 💸 Prices in whole won on every row, with deposit and monthly rent kept in separate fields, never merged

🎬 Quick Start

Pick a district, pick the deal type, press Start. The defaults return 강남구 sale apartments, so a run with no configuration at all still gives you real data. Everything below is optional narrowing.

curl -X POST 'https://api.apify.com/v2/acts/sian.agency~naver-property-scraper/runs?token=YOUR_TOKEN' \
-H 'Content-Type: application/json' \
-d '{"operation":"search","locations":["강남구"],"dealType":"sale","maxResults":100}'

🚀 Getting Started (3 Simple Steps)

Step 1: Choose your regions

District names (강남구, 수원시장안구) are the everyday choice; a neighbourhood (역삼동) narrows further; a whole city or province (서울시, 경기도) is a long run, so split it by district.

Step 2: Choose the deal type and the property types

Sale, jeonse, monthly rent or short-term: one per run, so the price column means one thing. Leave property types empty to sweep all 25, or pick apartments (A01), officetels (A02) and friends.

Step 3: Press Start, then export

Watch the run log count the pages. When it finishes, download JSON, CSV or Excel from the dataset, or open the HTML report for a summary with the listing links already collected.

That's it! In a few minutes, you'll have:

• Every matching listing with price, areas, floor, build year and brokerage
• The owner-verification badge and the brokerage count on each row
• A copy-ready list of listing links

📥 Input Configuration

Field	Type	Required	Description
operation	string	No	search (default) or detail
locations	array	No	Korean region names or Naver region codes; defaults to 강남구
dealType	string	No	sale (default), jeonse, monthly or shortterm
propertyTypes	array	No	Naver property-type codes (A01 = 아파트); empty means every type
maxResults	integer	No	Whole-run listing budget, default 100
includeDetails	boolean	No	Open each listing for the full record
minPrice / maxPrice	integer	No	Price bounds in whole won; 0 means no bound
minArea / maxArea	integer	No	Exclusive-area bounds in m²; 0 means no bound
onlyOwners	boolean	No	Keep only Naver's owner-verified listings (집주인 매물)
listingUrls	array	No	Naver listing numbers or addresses, for the detail operation

Example:

{
  "operation": "search",
  "dealType": "jeonse",
  "locations": ["강남구", "송파구"],
  "minPrice": 500000000,
  "maxPrice": 900000000,
  "maxResults": 200
}

🗺️ Coverage

All 16 Korean metropolitan cities and provinces and all 256 districts (시군구) Naver indexes, plus neighbourhood-level (읍면동) searches by name or Naver's own region code. All 25 property types Naver publishes: apartments, officetels, reconstructions and redevelopments, pre-sale rights, one-rooms, villas and row houses, detached houses, country houses, hanok, offices, shops, buildings, commercial premises, accommodation and condos, factories and warehouses, land, knowledge-industry centers, gosiwon and other. All four deal types: 매매 (sale), 전세 (jeonse deposit lease), 월세 (monthly rent) and 단기임대 (short-term). Naver caps a search's reachable depth: pagination follows the site's own cursor, and the run stops on the last full page or your max listings, whichever comes first.

📤 Output

Results are saved to the Apify dataset with 40+ fields, including:

Field	Type	Description
listingId	string	Naver listing number
url	string	Canonical listing address
buildingName	string	The complex or building, in Korean
dealType / dealTypeKo	string	Sale, jeonse, monthly or short-term (English / Korean)
price	number	Asking price in won, or the deposit for jeonse and monthly rows
rentPrice	number	The monthly rent on a monthly row, separate from the deposit
managementFee	number	The building's monthly management fee
areaExclusive / areaSupply	number	Exclusive (전용) and supply (공급) area in m²
floor / totalFloors	number	Floor number and floors in the building
buildYear	number	Year the building was completed
district / neighbourhood	string	Where the property is (구 / 동)
latitude / longitude	number	Exact coordinates
isOwnerVerified	boolean	Naver's own 집주인 매물 badge
brokerageName / brokerName	string	The brokerage that posted it
sameAddressCount	number	How many brokerages hold the same unit
featureText	string	The advertiser's short feature line (includeDetails)
roomCount / bathRoomCount	number	Rooms and bathrooms (includeDetails)
parkingCount	number	Parking spaces in the complex (includeDetails)

Example:

{
  "listingId": "2648400245",
  "url": "https://fin.land.naver.com/articles/2648400245",
  "buildingName": "빌폴라리스",
  "dealType": "Sale",
  "dealTypeKo": "매매",
  "price": 8000000000,
  "priceLabel": "80억",
  "areaExclusive": 166.01,
  "floor": 11,
  "totalFloors": 20,
  "buildYear": 2009,
  "district": "강남구",
  "neighbourhood": "청담동",
  "isOwnerVerified": true,
  "brokerageName": "청담더샤인공인중개사사무소",
  "sameAddressCount": 25,
  "confirmedDate": "2026-09-08"
}

💼 Use Cases

Seoul Asking-Price Index

Pull every sale and jeonse listing for a district and price the market before anyone drives there: asking price against exclusive area by 구, apartment stock by build year, and what a 84㎡ (34-pyeong) flat actually lists for in 강남구 against 송파구 or 마포구. Rows already carry price, both areas and the build year, so the per-pyeong arithmetic is done before the export lands.

Jeonse-to-Sale Ratio Monitoring

Korean tenants buy with a jeonse deposit, so the jeonse-to-sale price ratio is the number every landlord and tenant economy watch tracks. Run the same district twice, once for sale and once for jeonse, and the two datasets share complex numbers and areas, giving the ratio per complex without any matching work.

Owner-Verified Sourcing

Switch on 'Only owner-verified' and the run returns nothing but listings Naver has confirmed as posted by the home's owner (집주인 매물) — the direct-deal shortlist Korean buyers pay agents to find, and the reason they scroll the app by hand.

Brokerage Lead Generation

Every listing names the brokerage that posted it and how many other brokerages hold the same unit. Group a district by brokerage to see who holds the most live stock in a neighbourhood, then approach the ones with the deepest shelves.

New-Listing Monitoring

Naver stamps each listing with the date it was confirmed and exposed. Run a saved search on a schedule, keep the rows whose confirmation date moved past your last run, and you have the day's new stock for a district without paying for a duplicate feed.

Complex Deep-Dives

Search a neighbourhood, group by complex number, and one dataset yields the whole market story for a 단지: every unit type listed, at which floors and directions, at which prices, by how many brokerages, in a complex built when. It is the memo a buyer's agent writes by hand over a weekend.

🔗 Integration Examples

JavaScript/Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });

const run = await client.actor('sian.agency/naver-property-scraper').call({
  operation: 'search',
  dealType: 'sale',
  locations: ['강남구'],
  propertyTypes: ['A01'],
  maxResults: 200,
});

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('sian.agency/naver-property-scraper').call(
    run_input={
        'operation': 'search',
        'dealType': 'jeonse',
        'locations': ['강남구'],
        'maxResults': 200,
    }
)

for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item['buildingName'], item['price'], item['areaExclusive'])

cURL

curl -X POST 'https://api.apify.com/v2/acts/sian.agency~naver-property-scraper/runs?token=YOUR_TOKEN' \
-H 'Content-Type: application/json' \
-d '{"operation":"search","dealType":"sale","locations":["송파구"],"onlyOwners":true}'

Automation Workflows (N8N / Zapier / Make)

1. Trigger: a daily schedule, or a webhook from your own system
2. HTTP Request: call the actor's run-sync endpoint with your saved input
3. Process: filter the returned rows on price, district or the owner-verified badge
4. Action: append to a sheet, upsert into your CRM, or send the new listings to Slack

📊 Performance & Pricing

FREE Tier (Try It Now)

• 25 listings per run, with every field and every filter available
• No credit card required
• Enough to check the data before you commit to a sweep

PAID Tier (Production Ready)

• Unlimited listings per run
• Pay-per-result: charged per listing saved, never for a row your filters excluded
• Full record available as a per-listing add-on, only when you switch it on

💰 $2.70 per 1,000 listings, just under the best-positioned rival on the Store, with the owner-verification badge, brokerage counts and both area figures on the same row, and all four deal types in one actor.

🔗 View current pricing

❓ FAQ

Do I need a proxy or a browser for this?

No. Naver Real Estate refuses ordinary script traffic outright, and the actor handles the route itself the same way the official app gets its data — residential egress, session warm-up and per-call spacing are all wired in code. There is no proxy setting because which route to use is our cost decision, not something you should have to know.

What do I put in Regions?

Korean region names exactly as Naver spells them, or Naver's own region codes. District names (강남구, 송파구, 수원시장안구) are the everyday choice; a neighbourhood name (역삼동) narrows further; 서울시 or 경기도 reads the whole city or province and is best reserved for smaller sweeps.

What is the difference between a listing row and full details?

A listing row is everything Naver's feed puts on the card: price, complex, floor, areas, facing, build year, brokerage, verification badge and the short feature line. Full details opens the listing's own record and adds the untruncated feature text, the facility list, exact room and bath counts, parking totals, moving-in terms, photos and precise coordinates.

Are prices in won or 만원?

In whole won, exactly as the data carries them: a ₩4.4 billion apartment is 4400000000. Jeonse rows put the deposit in the price field; monthly-rent rows put the deposit in the price field and the monthly amount in a separate rent field. Divide by 10,000 yourself if your sheet thinks in 만원.

Can I compare sale and jeonse in one run?

Not in one run. Naver keeps the four deal types in separate feeds, and the actor reads one per run so the price column means one thing. Run it twice with the same regions and the two datasets share complex numbers, so matching them is one join.

How many listings can one search return?

Naver pages its feed 30 listings at a time and the actor walks that pagination until your max listings or the feed's own end. A district like 강남구 holds thousands of live listings, so pick property types or a price band to keep one run inside your budget; filtered-out rows are never billed.

What does 'owner-verified' mean?

Naver asks posters to prove they own the home and marks the listings that passed as 집주인 매물. The badge is Naver's own judgement, stored on the listing itself; switch on 'Only owner-verified' and the run keeps only those rows.

Will the Korean text come through correctly?

Yes. The feed is UTF-8 JSON and the actor reads it as UTF-8 end to end, so complex names, addresses, feature text and brokerage names arrive in the dataset, in the exports and in the run report exactly as Naver displays them.

🐛 Troubleshooting

The run says Naver Real Estate is pacing it

• The feed slows callers down for a minute or two at a time. The Actor spaces its calls, waits out the pause and picks up where it left off, so a paced run finishes late rather than short. If a run ends early on pacing, start it again in a few minutes.

A region name is not recognised

• Use the Korean name as Naver writes it (강남구, 해운대구). Every one of the country's districts is covered, and neighbourhood (동) names resolve too. If Naver's own search does not know the name, the Actor cannot search it either.

A listing URL is refused

• Paste the full listing address from your browser, not the bare listing number. The platform validates that field as a URL, so 1234567890 is refused before the run starts and never billed.

Sale and rent listings are not in the same dataset

• Naver keeps each deal type in its own feed, and one run reads one of them, so the price column always means the same thing. Run it once per deal type; the rows share complex numbers, so joining them afterwards is one step.

A search returns fewer rows than Max listings

• The feed matched fewer live listings than your ceiling. It pages 30 at a time and the run log prints what it walked, so a narrow district or a tight price band simply ends early. Rows you filtered out are never billed.

⚖️ Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses, gender, or location. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

Naver and Naver Real Estate (네이버 부동산) are trademarks of Naver Corporation. This Actor is not affiliated with, endorsed by, or sponsored by Naver Corporation.

🤝 Support

Join our active support community

• For issues or questions, open an issue in the actor's repository
• Check SIÁN Agency Store for more automation tools
• 📧 apify@sian-agency.online

---

Built by SIÁN Agency | More Tools