Hwahae Reviews Scraper
Pricing
from $0.02 / 1,000 review signal records
Hwahae Reviews Scraper
Scrape Hwahae ratings, review counts, rankings, prices, brands, discounts, and Korean beauty product URLs from public search pages.
Pricing
from $0.02 / 1,000 review signal records
Rating
0.0
(0)
Developer
Stas Persiianenko
Maintained by CommunityActor stats
0
Bookmarked
3
Total users
2
Monthly active users
4 days ago
Last modified
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Scrape Hwahae Korean beauty product review signals without logging in. This actor collects product and goods records from public Hwahae search and ranking pages, including ratings, review counts, brand names, prices, discounts, badges, and URLs.
What does Hwahae Reviews Scraper do?
Hwahae Reviews Scraper turns public Hwahae discovery pages into structured datasets for Korean beauty research.
It helps you monitor:
- ⭐ product ratings
- 💬 review counts
- 🧴 product and goods names
- 🏷️ brands and discounts
- 📈 ranking/search context
- 🖼️ images and public URLs
The actor focuses on reliable public search and ranking data. Hwahae product detail pages can show an AWS WAF challenge to direct HTTP clients, so the MVP avoids fragile detail-page review text and extracts stable review-summary signals instead.
Who is it for?
Cosmetics brands
Track how your products and competing products appear in Hwahae search results.
Ecommerce category analysts
Compare review volumes, ratings, prices, and discounts across Korean beauty categories.
Agencies and market researchers
Build repeatable Korean beauty monitoring workflows for clients.
Retail and merchandising teams
Spot high-review products, fast-moving goods, and promotional price signals.
Why use this actor?
Manual Hwahae research is slow when you need many keywords or category checks.
This actor gives you:
- ✅ structured product and goods rows
- ✅ Korean brand and product names
- ✅ review count and rating metrics
- ✅ prices, discounts, and sold-out flags
- ✅ repeatable runs for monitoring
- ✅ dataset export to JSON, CSV, Excel, and API
What data can you extract?
| Field | Description |
|---|---|
searchKeyword | Keyword used for a search run |
sourceUrl | API or page URL used as source |
itemType | goods, product, or ranking_product |
productId | Hwahae product identifier when available |
goodsId | Hwahae commerce goods identifier when available |
brandName | Public brand name |
productName | Product name |
goodsName | Commerce goods listing name |
rating | Average rating shown by Hwahae |
reviewCount | Public review count |
price | Current/discount price when available |
originalPrice | Original price when available |
discountRate | Discount percentage |
imageUrl | Product or goods image |
rank | Ranking/search rank when available |
badges | Hwahae commerce badges |
isSoldOut | Sold-out flag when available |
scrapedAt | ISO timestamp |
How much does it cost to scrape Hwahae review data?
This actor uses pay-per-event pricing.
- A small start event is charged once per run.
- A per-item event is charged for each saved record.
- You control spend with
maxItems.
For first tests, keep maxItems around 50.
Quick start
- Open the actor on Apify.
- Enter one or more Korean search keywords.
- Optionally add Hwahae search or ranking URLs.
- Set
maxItems. - Run the actor.
- Export the dataset.
Input options
Search keywords
Use Korean beauty terms, brands, or product names.
Examples:
토리든선크림수분크림클렌징오일
Start URLs
Use public Hwahae pages such as:
https://www.hwahae.co.kr/search?q=%ED%86%A0%EB%A6%AC%EB%93%A0https://www.hwahae.co.kr/rankings?english_name=category&theme_id=2
Maximum records
maxItems limits saved records across all keywords and URLs.
Example input
{"searchKeywords": ["토리든", "선크림"],"startUrls": [{ "url": "https://www.hwahae.co.kr/rankings?english_name=category&theme_id=2" }],"maxItems": 100}
Example output
{"searchKeyword": "토리든","sourceUrl": "https://gateway.hwahae.co.kr/v14/commerce/search/goods?...","itemType": "goods","goodsId": 54413,"goodsUrl": "https://www.hwahae.co.kr/goods/.../54413?goods_tab=review_ingredients","brandName": "토리든","goodsName": "[only화해] 다이브인 저분자 히알루론산 세럼 100ml","rating": 4.61,"reviewCount": 83328,"price": 27900,"discountRate": 36,"scrapedAt": "2026-07-01T00:00:00.000Z"}
Tips for better results
- Use Korean keywords for best recall.
- Combine brand and category terms.
- Use ranking URLs when you want category/trending context.
- Increase
maxItemsonly after a small test run succeeds. - Deduplicate downstream on
goodsIdorproductId.
Limitations
Hwahae product detail pages can trigger AWS WAF challenges for direct scrapers.
This actor intentionally extracts public search/ranking review signals instead of forcing fragile detail-page review text collection.
Integrations
Use the output with:
- Google Sheets for category monitoring
- BigQuery or Snowflake for trend analysis
- BI dashboards for Korean beauty reporting
- Alerts when review counts or ranks change
- Brand intelligence workflows
API usage with Node.js
import { ApifyClient } from 'apify-client';const client = new ApifyClient({ token: process.env.APIFY_TOKEN });const run = await client.actor('automation-lab/hwahae-reviews-scraper').call({searchKeywords: ['토리든', '선크림'],maxItems: 100,});console.log(run.defaultDatasetId);
API usage with Python
from apify_client import ApifyClientclient = ApifyClient('YOUR_APIFY_TOKEN')run = client.actor('automation-lab/hwahae-reviews-scraper').call(run_input={'searchKeywords': ['토리든', '선크림'],'maxItems': 100,})print(run['defaultDatasetId'])
API usage with cURL
curl -X POST "https://api.apify.com/v2/acts/automation-lab~hwahae-reviews-scraper/runs?token=$APIFY_TOKEN" \-H 'Content-Type: application/json' \-d '{"searchKeywords":["토리든","선크림"],"maxItems":100}'
MCP usage
Use this actor from Apify MCP:
https://mcp.apify.com/?tools=automation-lab/hwahae-reviews-scraper
Add it in Claude Code:
$claude mcp add apify-hwahae --url "https://mcp.apify.com/?tools=automation-lab/hwahae-reviews-scraper"
Or configure an MCP client with JSON:
{"mcpServers": {"apify-hwahae": {"url": "https://mcp.apify.com/?tools=automation-lab/hwahae-reviews-scraper"}}}
Example prompts:
- "Run Hwahae Reviews Scraper for 토리든 and summarize top products by review count."
- "Compare 선크림 products by rating and discount rate."
- "Export Hwahae category ranking data to a CSV."
Data quality notes
The actor uses public Hwahae API/page data and keeps raw identifiers where available.
Ratings and review counts are point-in-time values from Hwahae.
FAQ
Why do product detail pages not return full review text?
Hwahae detail pages may require a browser WAF token. This actor avoids that fragile path and uses public search/ranking data.
Why do I see fewer rows than expected?
The keyword may have fewer public goods results than maxItems. Add more keywords or ranking URLs.
Legality
Only scrape publicly available data and respect Hwahae's terms, privacy rules, and applicable laws.
Do not use the output for spam, harassment, or unauthorized profiling.
Related scrapers
Explore other automation-lab actors for ecommerce and market intelligence workflows:
- https://apify.com/automation-lab/google-shopping-scraper
- https://apify.com/automation-lab/amazon-products-scraper
- https://apify.com/automation-lab/product-review-scraper
Version notes
0.1
Initial release focused on public Hwahae search/ranking review signals.
Field mapping details
Search API rows are emitted as goods items.
Search page embedded product rows are emitted as product items.
Ranking embedded rows are emitted as ranking_product items.
Monitoring workflow
Run the same keywords daily or weekly.
Compare reviewCount, rating, price, and rank over time.
Alert when competitors gain review volume quickly.
Category workflow
Use broad category keywords such as 선크림, 토너, or 클렌징폼.
Sort by reviewCount to identify established winners.
Sort by discountRate to spot aggressive promotions.
Brand workflow
Use brand keywords such as 토리든.
Review which goods listings dominate search results.
Compare official goods, bundles, and promotions.
Export formats
Apify datasets can be exported as:
- JSON
- CSV
- Excel
- XML
- RSS
- API responses
Support
If a public Hwahae page changes or a keyword returns unexpected data, open an issue with the run input and run URL.