Scrape Product Data from Fashion Sites

Challenge

The customer required a product scraper to fetch the data from over a hundred fashion websites, such as GAP, Macy’s, and Nordstrom. Product data, as well as all conceivable variations of a specific product, such as assorted colors, were essential data fields. The customer gave us a range of source websites to crawl as well as the data points needed. The extraction interval was set at once a day.

Crawlers were put up to fetch the necessary data fields from the source sites by our team. Because the source websites were in varied formats and designs, this use case falls under our site scan service. The extracted data had to be saved in CSV format and transferred to the client’s S3 servers. The initial installation took only a few days, and the crawlers began delivering data right away.

During the initial crawl, almost 200 thousand records were sent to the client.

Solution

Client Requirements: The client supplied their data needs, which included a list of source websites, product pieces of information, and frequency of data extraction.

Custom Product Scraper Set Up: Crawlers were put up to scrape product information such as the product name, description, characteristics, price, and discounts for each color and size variant.

Data Delivery: The information was extracted through specially trained web crawlers and given to the customer in the frequency and file format that they requested directly to their S3 locations.

The data was massive, with over 1 million records collected and given in a clean and organized format every day.

iWeb Scraping Benefits

After the initial installation was finished, the client began getting data within a few days.

Our team handled all of the technical components of the process. We set up monitoring for the source websites to monitor any modifications that necessitated updates to the crawling arrangement.

iWeb Scraping’s efficient tech stack handled large volumes of data with ease.

After starting the data collecting project, the client was able to deploy their fashion app marketplace in a short time.

Conclusion

Our LinkedIn Post Data Analysis offered proof of how analytics-based data can revolutionize B2B content strategy. The shift toward structured performance data and less guesswork allowed the client to enhance the level of engagement, attract the right people, and produce more qualified leads. This case study demonstrates the knowledge of iWeb Scraping, which has the expertise of developing custom data extraction and analytics solutions on individual platforms. By being in 20+ industries, we assist businesses to maximize all the potential of the online presence with precise and useful real-time data insights.

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Robert Moris

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We approached iWeb Scraping for extracting product listings from an osCommerce-based website along with multiple eCommerce platforms. Their team delivered clean, structured, and highly accurate datasets that perfectly matched our requirements. The entire process was smooth and professional.

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I used iWeb Scraping services for an online job data extraction project, and the results were highly accurate and cost-effective. The data was delivered exactly as required, and I would definitely choose their services again for future data extraction needs.

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