How to use e-commerce crawling to identify fashion trends and utilize them for product planning

How do you decide which items to push in the next season?

I can sense what's selling well these days, but it's difficult to confirm with data.

In the fashion industry, trends change rapidly. Information such as which items are trending on online shopping malls, what promotions competitors are running, and what aspects customers are satisfied or dissatisfied with is essential for product planning.

However, there are challenges:

• Checking best-selling items from multiple shopping malls is cumbersome
• Missing out on competitor promotions and events
• Difficulty in systematically analyzing product reviews
• Lack of a system to track trend changes with data

Relying solely on the intuition and experience of individuals can lead to missing out on trends.

Collecting Fashion Trend Data through E-commerce Crawling

By using Hashscraper, you can automatically collect data on popular products, promotions, and reviews from major domestic online shopping malls.

Example of Actual Crawling Data - Weekly TOP100 Products

{
  "Channel": "무신사",
  "Category": "아우터",
  "Rank": "3",
  "Product Name": "오버핏 퀼팅 패딩 점퍼",
  "Brand": "OO",
  "Price": "89,000",
  "Original Price": "129,000",
  "Discount Rate": "31%",
  "Review Count": "1,247",
  "Rating": "4.8",
  "Collected Date": "2025-01-06"
}

Example of Actual Crawling Data - Product Reviews

{
  "Channel": "무신사",
  "Product Name": "오버핏 퀼팅 패딩 점퍼",
  "Rating": "5",
  "Review Body": "핏이 예쁘고 가벼워요. 다만 주머니가 좀 얕아서 물건 떨어질까 걱정됩니다.",
  "Review Date": "2025-01-05",
  "Reviewer Info": "165cm / 55kg / M 구매"
}

Regularly collecting rankings of popular products and customer reviews allows you to track trend changes with data.

Monitoring Competitor Promotions and Events

Promotions in fashion e-commerce directly impact sales. Understanding when and under what conditions competing platforms are offering discounts can help refine our promotion strategy.

Example of Actual Crawling Data - Promotions/Events

{
  "Channel": "W컨셉",
  "Event Type": "시즌오프",
  "Event Name": "WINTER SALE UP TO 70%",
  "Start Date": "2025-01-02",
  "End Date": "2025-01-15",
  "Target Category": "아우터, 니트, 코트",
  "Discount Range": "50~70%",
  "Promo Code": "WINTER70",
  "Min Purchase": "50,000원",
  "Collected Date": "2025-01-06"
}

{
  "Channel": "무신사",
  "Event Type": "브랜드 단독",
  "Event Name": "OO브랜드 신상 10% 쿠폰",
  "Start Date": "2025-01-05",
  "End Date": "2025-01-12",
  "Target Category": "전 상품",
  "Discount Range": "10%",
  "Promo Code": "NEWOO10",
  "Min Purchase": "30,000원",
  "Collected Date": "2025-01-06"
}

Promotion Data Items Available for Collection

Utilization of Promotion Data

By collecting competitor promotions on a daily basis, you can create an annual promotion calendar.

Use Case: Data-driven Product Planning for Fashion Companies

A domestic fashion company aimed to utilize data for product planning and marketing. The goal was to quickly grasp market trends, systematically analyze competitor trends and customer responses to their products.

Crawling Settings

• Target Channels: Musinsa, W Concept, 29CM, SSF Shop, Hanssem (5 shopping malls)
• Data Collection Items: Weekly TOP100 products, events/promotions, in-house product reviews
• Crawling Frequency: Weekly (daily for promotions)

Analyzed Data from Crawling

Quantitative Results

The collected data is summarized into weekly trend reports and shared with the product planning and marketing teams.

Utilization Examples of Collected Data

1. Early Discovery of Popular Items

Tracking weekly TOP100 ranking changes can help identify rapidly rising items early.

2. Product Improvement Based on Reviews

Identifying recurring complaints in reviews can guide improvements for future products.

Can Also Be Used in These Cases

Seasonal Planning

Accumulating data on popular items during the same period in past seasons can be used for next year's seasonal planning.

Launching New Brands

You can pre-determine popular price ranges and styles in the category you are entering.

Marketing Timing

Analyzing competitor promotion patterns can help determine the optimal timing for our promotions.

Data Integration Methods

The collected data is provided in raw data format, and you can choose the integration method according to the situation.

• Excel Download — raw data
• Email Sending — receive notifications on weekly TOP100 changes, competitor promotions
• API Integration — real-time integration into internal dashboards
• DB Integration — direct loading into internal analysis systems

Summary

Fashion trends first appear in online shopping mall data.

Collecting data through crawling allows you to plan products based on evidence rather than intuition.

Hashscraper handles crawler operation, maintenance, and monitoring. Even in the event of platform policy changes or data collection errors, there is no need for direct intervention from the client.

Get Started Now

With Hashscraper, you can automatically collect data on popular products, promotions, and reviews from online shopping malls.

Go to Musinsa Product Collection Bot

If you need crawling for other shopping malls or customized data collection, please contact us.

Inquire about Crawling