Musinsa Fashion Rankings Scraper

Export current Musinsa fashion rankings as clean, structured data. Track which products and brands are moving on Korea's leading fashion marketplace, compare KRW prices and discounts, and schedule repeat snapshots without running a browser.

This Actor reads Musinsa's public ranking data and saves one dataset row per ranked product. Every result includes source and filter context, so analysts can compare snapshots confidently.

What does Musinsa Fashion Rankings Scraper do?

It turns Musinsa's live product-ranking modules into export-ready records.

• 🏆 Collect rank, product ID, product name, and product URL.
• 🏷️ Capture brand ID, brand name, and brand URL.
• 💸 Compare original price, final price, discount amount, and discount rate in KRW.
• ⭐ Export review count and review score when Musinsa supplies them.
• 🔥 Preserve labels plus live viewer or buyer snippets.
• 🧭 Apply category, gender, age-band, period, and sold-out filters.
• 📅 Add a scrape timestamp and complete filter context to every row.

Who is it for?

K-fashion brands can monitor whether their products enter or leave important category rankings.

Retailers and resellers can identify fast-moving products and discounts before making buying decisions.

Merchandisers can compare audience segments, category leaders, and price bands.

Market-research teams can schedule snapshots and build historical trend datasets.

Data teams can feed structured Musinsa ranking data into warehouses, dashboards, spreadsheets, or alerting systems.

Why use this Musinsa ranking scraper?

Musinsa's ranking page is useful for shoppers but not designed for repeated analysis. Copying records manually is slow, inconsistent, and difficult to automate.

This Actor gives you:

• consistent field names across runs;
• strict maxItems cost control;
• deduplication by Musinsa product ID;
• source URLs for auditability;
• JSON, CSV, Excel, XML, RSS, and API access through Apify datasets;
• fail-closed behavior when a requested ranking signal is unavailable.

What Musinsa data can I extract?

Field	Meaning
rank	Position shown by Musinsa
productId	Stable Musinsa product identifier
productName	Product title
productUrl	Canonical product page
brandId	Musinsa brand identifier
brandName	Displayed Korean brand name
brandUrl	Brand page when provided
imageUrl	Product image
currency	KRW
originalPrice	Price before discount
finalPrice	Current displayed price
discountAmount	Calculated original minus final price
discountRate	Displayed discount percentage
reviewCount	Number of reviews
reviewScore	Musinsa review score
soldOut	Whether the card is sold out
labels	Product and sales labels
salesSnippets	Live viewing or buying text
categoryId	Applied category identifier
appliedTab	Ranking tab reported by Musinsa
filters	Exact run filter context
sourceUrl	Public JSON URL used for the row
scrapedAt	UTC extraction timestamp

Supported ranking modes

Set rankingType to one of:

• overall — request Musinsa's page-advertised overall source section (199);
• new — request the distinct NEW source section (200);
• rising — request the distinct rising source section (201).

Every row must match both the selected source URL and that source's applied-tab signal. The Actor never treats a label or shared tab value from an overall feed as proof that a product is a new arrival.

Category filters

The Actor selects the source section from rankingType. The default categoryCode is 000, meaning all categories.

Common main-store category codes include:

• 001 — tops;
• 002 — outerwear;
• 003 — pants;
• 004 — bags;
• 100 — dresses and skirts;
• 005 — fashion accessories;
• 018 — sneakers;
• 104 — beauty.

Musinsa controls these identifiers. Use category codes advertised on the current ranking page.

Audience and period filters

Choose all, men, or women with gender. Segment rankings by all ages, under 20, five-year age bands from 20 through 39, or 40+.

Use period for real-time, daily, weekly, or monthly ranking windows. The returned filters object records the exact choice in every result.

How to scrape Musinsa rankings

1. Open the Actor input page.
2. Choose an overall, new, or rising ranking.
3. Keep category 000 for a broad first run.
4. Optionally select gender, age band, period, and sold-out behavior.
5. Set a low maxItems while testing.
6. Click Start.
7. Open the dataset and export in your preferred format.

Input example

{
  "rankingType": "overall",
  "categoryCode": "001",
  "gender": "F",
  "ageBand": "AGE_BAND_25",
  "period": "WEEKLY",
  "includeSoldOut": false,
  "maxItems": 50
}

Output example

{
  "rank": 1,
  "productId": "6064531",
  "productName": "Example ranked product",
  "productUrl": "https://www.musinsa.com/products/6064531",
  "brandId": "example-brand",
  "brandName": "예시 브랜드",
  "currency": "KRW",
  "originalPrice": 69000,
  "finalPrice": 34500,
  "discountAmount": 34500,
  "discountRate": 50,
  "reviewCount": 104,
  "reviewScore": 98,
  "soldOut": false,
  "labels": [],
  "salesSnippets": ["207명이 보는 중"],
  "filters": {
    "rankingType": "overall",
    "sectionId": "199",
    "categoryCode": "001",
    "gender": "F",
    "ageBand": "AGE_BAND_25",
    "period": "WEEKLY",
    "includeSoldOut": false
  },
  "scrapedAt": "2026-07-19T07:00:00.000Z"
}

Actual products and values change as Musinsa updates its rankings.

How much does it cost to scrape Musinsa rankings?

This Actor uses pay-per-event pricing: a small fee when a run starts and a tiered fee for each saved ranking product. Higher Apify plans receive lower per-product prices.

The default input saves only 30 products, while the input form prefill uses 10 for a cheap first test. Check the live Actor pricing tab for the exact price attached to your Apify plan.

Scheduling a Musinsa ranking monitor

Create an Apify schedule to run the same input hourly, daily, or weekly. Export each run to a warehouse or use dataset webhooks to notify another system.

A useful monitoring key is productId. Compare rank, final price, discount rate, labels, and sold-out state between snapshots.

Trend-analysis workflow

For category trend analysis:

1. run one category per schedule;
2. keep gender and age filters stable;
3. store scrapedAt and filters with every row;
4. calculate rank movement by productId;
5. aggregate brand share by brandId;
6. alert when a product enters the top 10 or its discount changes.

Price-intelligence workflow

Use originalPrice, finalPrice, discountAmount, and discountRate together. A ranking snapshot can reveal price bands and promotion intensity without visiting each product detail page.

The Actor reports the price shown on the ranking card. It does not calculate delivery fees, member-only coupons, or checkout totals.

Apify integrations

Connect results to:

• Google Sheets for buyer and merchandising reviews;
• Slack for top-10 or rising-product alerts;
• Make or Zapier for no-code workflows;
• webhooks for immediate post-run processing;
• Amazon S3 or Google Drive for snapshot archives;
• BigQuery, Snowflake, or another warehouse for historical analysis.

JavaScript API example

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/musinsa-fashion-rankings-scraper').call({
  rankingType: 'overall',
  categoryCode: '001',
  gender: 'F',
  period: 'REALTIME',
  maxItems: 50,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python API example

from apify_client import ApifyClient
import os

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('automation-lab/musinsa-fashion-rankings-scraper').call(run_input={
    'rankingType': 'overall',
    'categoryCode': '000',
    'period': 'WEEKLY',
    'maxItems': 100,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)

cURL API example

curl -X POST \
  "https://api.apify.com/v2/acts/automation-lab~musinsa-fashion-rankings-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"rankingType":"overall","categoryCode":"000","maxItems":30}'

Use with Apify MCP

Connect the Actor to AI assistants through Apify MCP.

Claude Code setup:

$claude mcp add --transport http apify "https://mcp.apify.com/?tools=automation-lab/musinsa-fashion-rankings-scraper"

Claude Desktop setup: add this server to the Claude Desktop MCP configuration.

Cursor setup: add the same HTTP URL in Cursor Settings → MCP.

VS Code setup: add the same HTTP URL to your workspace MCP server configuration.

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=automation-lab/musinsa-fashion-rankings-scraper"
    }
  }
}

Example prompts:

• “Export the top 30 Musinsa women's tops and summarize the leading brands.”
• “Compare weekly discounts in the overall Musinsa ranking.”
• “Create a table of rank, product, brand, KRW price, and review count.”

Data quality and reliability

The Actor maps each ranking mode to its page-advertised source section and validates category identifiers before sending a request. It fails non-zero if Musinsa returns no matching product cards, preventing a structural source change from looking like a successful empty scrape.

Products are deduplicated by productId. Sequential requests and strict item limits reduce unnecessary load.

Limitations

• Musinsa can change its public modules, category IDs, labels, or ranking logic.
• Source section IDs and applied-tab names can change if Musinsa redesigns rankings.
• Review fields may be absent on some cards.
• Ranking-card prices may differ from checkout prices or targeted coupons.
• The Actor exports rankings, not complete product detail pages or inventory variants.
• Korean labels and product names are preserved as supplied.

Tips for best results

• Start with overall and category 000.
• Test unknown category codes with a small maxItems.
• Keep filter settings fixed when comparing snapshots.
• Use product IDs, not translated names, as historical keys.
• Schedule weekly mode weekly and real-time mode more frequently.
• Store raw labels because Musinsa may introduce new popularity signals.

Is scraping Musinsa legal?

This Actor accesses publicly available ranking data without logging in. Web scraping laws and website terms vary by jurisdiction and use case.

You are responsible for using the data lawfully, respecting applicable terms, intellectual-property rights, privacy obligations, and reasonable request rates. Do not use the Actor to collect private account data or bypass access controls.

Troubleshooting

Why did a new or rising run fail with no matching products?

Musinsa did not return cards carrying the expected source-tab signal for that page-advertised route. Try a broader category or another period. The failure is intentional and avoids misleading output.

Why did a category return no records?

Confirm the categoryCode is currently advertised by Musinsa for the selected ranking type. Category availability can differ between Overall, NEW, and Rising tabs.

Why are some review or brand fields missing?

Musinsa does not include every optional field on every product card. The Actor preserves available values rather than inventing defaults.

FAQ

Does the Actor require a Musinsa account?

No. The supported ranking scope is public and anonymous.

Does it run a browser?

No. It uses the JSON data route advertised by Musinsa's ranking page, so it is faster and cheaper than browser automation.

Can it return more than 100 products?

Yes, when Musinsa supplies a next link for the selected ranking. maxItems is capped at 500 to keep runs bounded.

Can I translate Korean names automatically?

The Actor preserves source text for accuracy. Translate downstream with your preferred translation service.

Can it scrape full product details or variants?

No. Version 1 focuses on ranking intelligence. Product URLs and IDs can feed a separate product-detail workflow.

How fresh are the results?

Freshness follows the selected Musinsa period and Musinsa's own ranking update schedule. scrapedAt records when this Actor fetched the snapshot.

Related scrapers

Combine ranking data with other Automation Lab actors when you need broader research:

• Google Search Results Scraper for open-web brand research.
• Website Screenshot Generator for visual monitoring of public pages.
• URL Metadata Extractor for enriching product and brand links.

Check each related Actor's current Store page and input contract before building a workflow.

Support

If a run fails, share the run ID, non-sensitive input, selected section/category codes, and the relevant log message through the Actor's Issues tab. This makes source changes faster to diagnose.