Naver Reviews Scraper (네이버 리뷰) | Smart Store and Brand Store Product Reviews (2026)

From SilentFlow. Creators of Pinterest Scraper (#1 for “pinterest pins scraper” in Apify Store search) and Leboncoin Scraper Ppe, with 230,000+ combined lifetime runs.

Every buyer review of the Naver Shopping products you care about, one row per review, from a single Korean keyword or a product address. Our test run turned the keyword 유기농 사과 (organic apples) into 100 reviews of 7 products in 13 seconds, each with its rating, full text, option bought, photos, AI tags, buyer profile and the seller's reply, with no Naver account.

Why choose this actor?

Hunting down product links before you can read a single review? Clicking through Korean review tabs twenty reviews at a time? Reading one product's reviews when you needed the whole category's?

• Start from a keyword, not a list of product links. Type 유기농 사과 and the run finds the Smart Store and Brand Store products Naver shows first for it, then reads their reviews product after product: in our test, 44 reviewed products found and 100 reviews of the first 7 saved in 13 seconds. Product addresses and bare product ids work too, in the same form. The most used Naver Shopping review scraper takes product URLs only.
• Nothing to fill in before you press Start. No field is required: the form opens with a keyword already in place and runs as is. The most used Naver Shopping review scraper will not start until you paste product URLs into its required field.
• Seven form fields, every Naver filter kept. Keywords, product addresses, two limits, then the sort, the star ratings and one review type menu that holds Naver's own tabs (photo and video, one-month use, repeat buyers, store picks). The most used Naver Shopping review scraper spreads the same choices over eight fields, four of them separate on or off switches.

Try your first 100 reviews

Paste this input in the JSON tab of the Input page and press Start. It reads the reviews of the organic apple products Naver Shopping ranks first, twenty per product, in Naver's own ranking order.

{
  "keywords": ["유기농 사과"],
  "maxItems": 100,
  "maxReviewsPerProduct": 20,
  "sortBy": "ranking"
}

It runs on the Apify Free plan. Each review becomes one row of your dataset: open the Output tab to see the table, switch to the Details view for the option bought, AI tags, buyer profile and seller reply, or export the rows as JSON, CSV or Excel.

SilentFlow · Naver suite
Naver Scraper Shopping Products, Prices	Naver Reviews Scraper You are here

Copy to your AI assistant

Paste this block into Claude, ChatGPT or Cursor to give it the full picture of this scraper:

You have access to the Naver Reviews Scraper on Apify: silentflow/naver-reviews-scraper

It reads the buyer reviews of Naver Shopping products sold on Smart Store (스마트스토어)
and Brand Store (브랜드스토어), without a Naver account, and returns one row per review.

Input schema (no field is required, at least one keyword or one product address is needed):
- keywords (array of strings): searches on Naver Shopping, Korean works best ("유기농 사과").
  The run reads the reviews of the Smart Store and Brand Store products Naver shows first.
- productUrls (array of strings): product addresses (https://smartstore.naver.com/{store}/products/{id},
  https://brand.naver.com/{brand}/products/{id}, mobile m. addresses too) or bare product ids.
- maxItems (integer, default 100): max reviews for the whole run.
- maxReviewsPerProduct (integer, default 20): reviews read per product, 0 = all of them.
- sortBy (string, default "ranking"): ranking | newest | highest | lowest.
- starRatings (array of strings, default []): keep only these ratings, "1" to "5".
- reviewFilter (string, default "all"): all | photo_video | after_use | repurchase | store_pick.

Output per review (34 fields):
- id (string, Naver review id), url (string, the review's own page), productId (string),
  productName (string), productUrl (string, product page)
- rating (integer 1-5), text (string|null), optionPurchased (string|null)
- reviewType ("normal" | "after_use"), contentType ("text" | "photo" | "video")
- tags (array of strings, Naver AI tags), buyerInfo (array of strings, buyer profile answers)
- isRepurchase, isFreeTrial, isBestReview (booleans)
- sellerReply (string|null), sellerReplyAt (RFC 3339|null)
- author (string, masked by Naver), authorAvatarUrl (string|null), helpfulCount (integer)
- productRating (number), productReviewsCount (integer), productPrice (number), currency ("KRW")
- storeName (string), storeUrl (string)
- publishedAt (RFC 3339), modifiedAt (RFC 3339|null)
- images (array of URLs), videos (array of {thumbnailUrl, videoId}), productImageUrl (string)
- categoryId (string), keyword (string|null), scrapedAt (RFC 3339)

Use apify-client for Python or JavaScript: client.actor("silentflow/naver-reviews-scraper").call(run_input=...).

How to scrape Naver Shopping reviews

Three inputs, from the simplest to the most complete. Each one runs as is.

Get the reviews of a category from one keyword

{
  "keywords": ["유기농 사과"]
}

The reviews of the Smart Store and Brand Store products Naver shows first for the keyword, twenty per product, up to 100 in all. In our test this input returned 100 reviews of 7 products in 13 seconds. Korean keywords return the most products; brand and model names work in English.

Pull the negative photo reviews of a category, worst first

{
  "keywords": ["무선 선풍기"],
  "maxItems": 60,
  "maxReviewsPerProduct": 30,
  "sortBy": "lowest",
  "starRatings": ["1", "2"],
  "reviewFilter": "photo_video"
}

Only the one and two star reviews that come with photos or videos, lowest rating first, for the cordless fans Naver ranks first. In our test this input returned 60 reviews in 12 seconds, all rated 1 or 2, 52 with photos and 8 with videos, and 43 of them already answered by the seller.

Read every review of the products you follow, newest first

{
  "productUrls": [
    "https://smartstore.naver.com/pasteur365/products/11150965069",
    "https://brand.naver.com/lumena/products/13244298880",
    "6272899246"
  ],
  "maxItems": 1000,
  "maxReviewsPerProduct": 0,
  "sortBy": "newest"
}

A product address from your browser or the bare id at its end. maxReviewsPerProduct: 0 reads every review of each product, newest first, until maxItems. With a keyword instead, the same settings gave us 150 reviews of one product in 7 seconds, in date order.

Input parameters

Parameter	Type	Default	Description
keywords	array of strings	prefilled with 유기농 사과	Searches on Naver Shopping, one per line. The run reads the reviews of the Smart Store and Brand Store products Naver shows first for each keyword; our test keyword gave 44 reviewed products.
productUrls	array of strings	none	Product addresses or bare product ids. See the formats below.
maxItems	integer	100	Max reviews for the whole run, keywords and products together. No fixed limit.
maxReviewsPerProduct	integer	20	Reviews read per product before moving to the next one. 0 reads all of them.
sortBy	string	ranking	ranking (랭킹순), newest (최신순), highest (평점 높은순) or lowest (평점 낮은순).
starRatings	array of strings	all ratings	Keep only these ratings, from "1" to "5". A product's quota is shared between the ratings you pick.
reviewFilter	string	all	photo_video (포토/동영상), after_use (한달사용리뷰, one-month-use reviews), repurchase (재구매, repeat buyers) or store_pick (스토어PICK).

Accepted product formats:

• Smart Store product: https://smartstore.naver.com/pasteur365/products/11150965069
• Brand Store product: https://brand.naver.com/lumena/products/13244298880
• Mobile addresses: https://m.smartstore.naver.com/... and https://m.brand.naver.com/..., with or without tracking parameters
• Bare product id: 11150965069, the number at the end of the address

A price comparison page (search.shopping.naver.com/catalog/...) is not a store product: search the product's name as a keyword instead. An address that is not a Smart Store or Brand Store product is skipped and named in the log, and the rest of the input still runs.

What data can you extract from Naver?

Each row is one review, with 34 top-level fields grouped the way you read them. On our default run, 30 of them carry a value on at least half the rows and 27 on every row.

Group	Fields
Identity (5)	id (Naver's review id, stable), url (the review's own page on Naver Shopping), productId (the number in the product address), productName, productUrl (the product page)
Review (12)	rating, text, optionPurchased, reviewType, contentType, tags, buyerInfo, isRepurchase, isFreeTrial, isBestReview, sellerReply, sellerReplyAt
Buyer (3)	author (masked by Naver), authorAvatarUrl, helpfulCount
Product and store (6)	productRating, productReviewsCount, productPrice, currency, storeName, storeUrl
Time (2)	publishedAt, modifiedAt, both RFC 3339 UTC
Media (3)	images (review photos), videos (poster image and Naver video id), productImageUrl
Meta (3)	categoryId (Naver's leaf category), keyword (the search that found the product), scrapedAt

What the values look like:

• The option bought is on the row. optionPurchased: "선택: 가정용 2.7kg" tells you which size, color or flavor the buyer is talking about, so you can split feedback per variant.
• AI tags come with their words. tags: ["포장이 깔끔해요", "사과가 맛있어요"] ("neatly packed", "tasty apples") are the topics Naver's AI found in the review, named as Naver names them on the product page. In our default run, 42 of 100 reviews had at least one.
• The buyer's profile is kept. buyerInfo: ["2인", "신혼/부부", "다이어트"] (two people, newlyweds, on a diet) are the answers the buyer gave to Naver's review questions, when they gave any.
• The seller's answer ships with the review. sellerReply and sellerReplyAt hold the store's official reply; 71 of our 100 default reviews had one, and 43 of 60 in the negative photo run.
• Review kinds are words, not codes. reviewType is normal or after_use (a 한달사용리뷰 written after a month of use), contentType is text, photo or video.
• Numbers are numbers. rating: 5, helpfulCount: 3, productPrice: 41000 with currency: "KRW", productRating: 4.88.
• Every review has its own link. url opens the review on Naver Shopping (https://content.shopping.naver.com/reviews/5063312693), productUrl the product it belongs to.
• Absent is null or an empty list. A review without a seller reply has sellerReply: null; a review without photos has images: [].

Output example

A real row from the default run:

{
  "id": "5063312693",
  "url": "https://content.shopping.naver.com/reviews/5063312693",
  "productId": "12346845916",
  "productName": "유기농 홍로 사과 2.5kg 충북 음성 산지직송 특 2.5kg 가정용 2.7kg",
  "productUrl": "https://smartstore.naver.com/ecoapplefarmers/products/12346845916",
  "rating": 5,
  "text": "사과 먹고 싶어서 오랜만에 주문했는데 포장상태부터 깔끔하니 기분이 좋아요\n\n사과도 너무 맛있고, 껍질 먹는거 좋아하는데\n여기는 껍질 채 안심하고 먹을 수 있어 너무 만족스럽습니다",
  "optionPurchased": "선택: 가정용 2.7kg",
  "reviewType": "normal",
  "contentType": "video",
  "tags": ["포장이 깔끔해요", "사과가 맛있어요"],
  "buyerInfo": ["2인", "신혼/부부", "다이어트"],
  "isRepurchase": false,
  "isFreeTrial": false,
  "isBestReview": false,
  "sellerReply": "안녕하세요, 고객님\n상세한 구매후기를 남겨주셔서 감사합니다!\n저희 제품에 대해서 만족스럽게 느껴주시다니, 너무 기쁩니다.\n껍질에도 항산화 성분들이 많이 함유되어 있어서, 껍질째 드시면 건강에 도움이 될수 있습니다.\n소중한 후기 남겨주셔서 감사드리며, \n앞으로도 맛있고 좋은 사과로 보답할 수 있는 에코애플파머스가 되겠습니다. 😊",
  "sellerReplyAt": "2026-09-14T05:27:03Z",
  "author": "hell******",
  "authorAvatarUrl": "https://phinf.pstatic.net/contact/20250103_166/1735905783759Lc25X_JPEG/image.jpg",
  "helpfulCount": 3,
  "productRating": 4.88,
  "productReviewsCount": 69,
  "productPrice": 41000,
  "currency": "KRW",
  "storeName": "에코애플 파머스",
  "storeUrl": "https://smartstore.naver.com/ecoapplefarmers",
  "publishedAt": "2026-09-12T10:12:57Z",
  "modifiedAt": null,
  "images": [
    "https://phinf.pstatic.net/checkout.phinf/20260912_130/1789207857506oTlkl_JPEG/IMG_2974.jpeg",
    "https://phinf.pstatic.net/checkout.phinf/20260912_115/1789207861134Q9hvE_JPEG/IMG_2975.jpeg",
    "https://phinf.pstatic.net/checkout.phinf/20260912_61/1789207862364OpeFN_JPEG/IMG_2977.jpeg",
    "https://phinf.pstatic.net/checkout.phinf/20260912_153/1789207862509DOwiP_JPEG/IMG_2976.jpeg"
  ],
  "videos": [
    {
      "thumbnailUrl": "https://phinf.pstatic.net/image.nmv/shopnbuyer_2026_09_12_1209/I74zgeuNl9_03.jpg",
      "videoId": "3C32A886823C8735F9A28771F5DF78EC0AB3"
    }
  ],
  "productImageUrl": "https://shopping-phinf.pstatic.net/main_8989135/89891356633.2.jpg",
  "categoryId": "50002160",
  "keyword": "유기농 사과",
  "scrapedAt": "2026-09-26T09:29:26Z"
}

Advanced usage

Five recipes the examples above do not show. Each input runs as is.

Watch the new reviews of a category every morning

{
  "keywords": ["그릭요거트", "멸균우유"],
  "maxItems": 200,
  "maxReviewsPerProduct": 10,
  "sortBy": "newest"
}

Save it as a task and schedule it daily. Newest first with ten reviews per product gives you the latest reviews of the top products of each keyword: in our test, 200 reviews of 20 products in 31 seconds. The review id is stable, so keep the ids you already have and alert on the new ones.

Collect the one-month-use reviews of a product line

{
  "keywords": ["냉각 선풍기"],
  "maxItems": 150,
  "maxReviewsPerProduct": 30,
  "reviewFilter": "after_use"
}

한달사용리뷰 are written by buyers after a month with the product, so they talk about durability, battery and noise rather than delivery. In our test this input returned 150 of them, from 8 products, in 15 seconds. Set reviewFilter to repurchase instead to hear only from repeat buyers.

Gather buyer photos for a mood board or a UGC review

{
  "keywords": ["수제 비누"],
  "maxItems": 100,
  "maxReviewsPerProduct": 25,
  "sortBy": "highest",
  "reviewFilter": "photo_video"
}

Only reviews with photos or videos, best ratings first. Every row carries the photo links in images and the video posters in videos, next to the text and the option bought. In our test, 100 reviews of 5 products in 11 seconds, every one with a photo or a video.

Compare your product with its competitors, star by star

{
  "productUrls": [
    "https://smartstore.naver.com/pasteur365/products/11150965069",
    "https://brand.naver.com/lumena/products/13244298880"
  ],
  "maxItems": 400,
  "maxReviewsPerProduct": 200,
  "starRatings": ["1", "2", "3"]
}

The one to three star reviews of each product: the 200 per product are shared between the three ratings, up to 67 each, and a rating with fewer reviews leaves its share to the next. Group the rows by productName and rating in a spreadsheet to see which complaints each product draws, and read sellerReply to see how each store answers them.

Feed a sentiment model with balanced ratings

{
  "keywords": ["무선 이어폰"],
  "maxItems": 500,
  "maxReviewsPerProduct": 50,
  "starRatings": ["1", "2", "3", "4", "5"]
}

Picking all five ratings splits each product's quota between them, and a rating a product has too few reviews of leaves its share to the next, so the low ratings are not drowned by the five star majority. In our test this input returned 500 reviews of 10 products in 47 seconds: 155 five star, 123 four, 106 three, 56 two and 60 one star. Export the dataset as JSON or CSV and keep text, rating, tags and optionPurchased.

FAQ

What is Naver Shopping, and what are Smart Store and Brand Store? Naver (네이버) is Korea's largest search engine and Naver Shopping its shopping search. Most products it lists are sold on Smart Store (스마트스토어), Naver's platform for independent sellers, or Brand Store (브랜드스토어), its official brand shops. This scraper reads the buyer reviews (네이버 리뷰) of those products. Naver Map and Place reviews of restaurants and shops are a different service and are not covered.

Do I need a Naver account or an API key? No. The scraper reads the reviews any visitor sees on a product page, without logging in. You only give it keywords or product addresses.

Can I search in English? Yes. Brand and model names such as galaxy buds work. Korean keywords (유기농 사과, 무선 선풍기) return the most products because sellers title their listings in Korean. Review texts come back in the buyer's own words, mostly Korean.

How many reviews can I get? As many as you set in maxItems, with no fixed limit. A keyword gives the reviewed products Naver shows first for it (44 for 유기농 사과 in our test), and maxReviewsPerProduct decides how many reviews each of them gives. Set it to 0 with a product address to read every review of that product. Naver's own review tab stops at 20,000 reviews for one sort and filter.

How fresh is the data? Live. Every run reads Naver at that moment: a review posted a minute before the run is in it with sortBy: "newest", and ratings and review counts are the current ones.

Can I combine the filters? Yes, they add up. sortBy: "lowest", starRatings: ["1", "2"] and reviewFilter: "photo_video" returns the one and two star reviews with photos or videos, worst first. In our test on 무선 선풍기, 60 of them in 12 seconds.

Why do some rows have no photos, tags or seller reply? Because the review has none: the buyer posted no photo, Naver's AI found no topic, or the store did not answer. The field is an empty list or null and the row still ships. In our default run, 72 of 100 reviews had photos, 42 had AI tags and 71 had a seller reply.

Why is the author name cut with stars? Naver masks every reviewer id on its product pages (hell******). The scraper returns it exactly as Naver shows it and never tries to reveal it.

Which links are permanent? url (the review's own page on content.shopping.naver.com), productUrl, storeUrl and the review id stay valid as long as the review and the product exist. Photo and avatar links point to Naver's image server and work while the review is online: download the photos you want to keep.

Can I read the reviews of a price comparison page? Not directly. A search.shopping.naver.com/catalog/... page groups the offers of many sellers. Search the product's name as a keyword: the Smart Store and Brand Store offers come back with their own reviews.

How do I get the data into my tools? Every run's dataset exports to JSON, CSV, Excel, XML or RSS from the Output tab, or from the API: https://api.apify.com/v2/datasets/{DATASET_ID}/items?format=csv. Apify integrations send it to Google Sheets, Slack, Zapier, Make or a webhook.

Is it legal to scrape Naver reviews? The scraper reads public reviews that anyone can see in a browser without logging in. How you use them is up to you: see the Legal compliance section below.

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Support

Need something this scraper doesn't do yet? We ship features fast.

• Feature requests go straight to our backlog
• Enterprise needs? We do custom integrations and high-volume plans
• Pricing questions? Check the Monetization tab on the actor page

Response time: usually under 24 hours.

Legal compliance

This Actor extracts publicly available reviews from Naver Shopping (smartstore.naver.com and brand.naver.com). It does not bypass any login, paywall or CAPTCHA, and never uses a Naver account. Users are responsible for complying with Naver's terms of service and applicable data protection laws (GDPR, CCPA, PIPA in Korea, and PIPL where relevant). Rows carry reviewer ids masked by Naver, avatars and buyer profile answers, which can be personal data: handle them accordingly, keep only what you need, and honor removal requests. The data returned is informational; verify accuracy for regulated use cases.

Naver Reviews Scraper by SilentFlow: Smart Store and Brand Store reviews from a keyword or a product address, ready for your spreadsheet.