Case Study: Automating Fashion Trend Analysis with Web Scraping for 300% Increased Efficiency
Predicting and analyzing constantly changing fashion trends is based on experience, intuition, and comprehensive insights based on data. Especially, product information from online shopping malls and consumer reviews on those products are crucial sources for fashion trend analysis. If a company like Company A, which publishes a fashion trend magazine monthly, wants to collect such data in real-time, they must collect that data.
However, imagine this. How much time and manpower would be needed if thousands or even tens of thousands of product information and reviews were collected manually by people? Now, with web scraping, you can collect massive amounts of data without human intervention.
Web scraping is a technology that automatically retrieves desired data from web pages. In the past, people had to visit web pages manually and copy and paste the necessary information, but with web scraping technology, you can accomplish such cumbersome tasks in just a few minutes.
Let's introduce a case study of Company A, a fashion trend analysis company that automated fashion data collection through Hashscraper's web scraping service.
1. Before & After
Issue: We are short on time to analyze data, yet we collect data manually overnight.
Company A, which collects and analyzes data from online shopping malls to publish a fashion trend magazine regularly, was manually collecting data.
For example, they were going into Musinsa, looking at high-selling products one by one, and copying and pasting them into Excel. Moreover, it was impossible to go through tens of thousands of reviews to check consumer reactions.
Because they spent all their time collecting data before analyzing it, they were always chasing deadlines and couldn't afford to hire multiple part-time workers.
To solve these issues, Company A decided to introduce Hashscraper.
Solution: In just a few minutes, we can collect massive fashion data in the desired format, even if the number of products increases!
Hashscraper set up bots to collect data from the shopping malls monitored by Company A, and when the responsible person decides which category to collect, the bots automatically create Excel files with product information and reviews for that category, making it very convenient.
Since the Excel format is customized, there is no need for post-processing or additional processing after receiving the file. Now, employees no longer need to waste time collecting data and can focus more on analysis.
2. Hashscraper Musinsa Product Collection Bot Guide
In the Hashscraper dashboard, there are crawling bots set up to extract product information from Musinsa. Anyone can try it out with the 50,000 credits provided upon registration. By informing the bot of the Musinsa category, sorting criteria, and pages to collect, you can obtain product information that meets these conditions.
The resulting data includes various information such as category, sorting criteria, product URL, product name, hashtags, brand, item number, season, price information, and delivery information. Once the collection is complete, you can easily download it in Excel format.
In addition to the Musinsa product collection bot, the dashboard provides bots for collecting product information from various online shopping malls such as Naver Shopping, The Handsome, Musinsa, New Balance, Coupang, SSG.COM, and more. Extract the desired data with just a few simple clicks without the need for coding!
If there is no bot available for the site you want to collect from, leave your requirements through the inquiry form. Consultants with experience collecting data from over 4,000 domestic and international shopping malls will propose the best solution to solve your difficulties.
Also, check out this article:
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