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Rakuten is one of the leading eCommerce platforms in Japan and across Asia, offering a wide range of products from electronics, fashion, beauty, home appliances, and more. With millions of products listed and a vast user base, Rakuten has become a valuable source of product data for sellers, marketers, and researchers looking to analyze market trends, pricing strategies, and consumer preferences. In this blog, we will discuss how you can scrape Rakuten product lists easily and extract them in a structured format like Excel, CSV, or JSON to gain actionable insights for your eCommerce business. Why Scraping Rakuten Product Data is Useful Rakuten has millions of monthly users and thousands of sellers, making it a goldmine of eCommerce data. By scraping product data from Rakuten, you can: Analyze product trends: Understand which products are popular among buyers and which categories are gaining traction. Monitor competitor pricing: Stay competitive by tracking the prices of similar pro...

Just a few days after its release, ChatGPT reached over one million users , and within two months, that number grew to 100 million active users, making it the second fastest-growing consumer app in history. In less than a year, it hit 100 million weekly users, and the number keeps climbing. ChatGPT’s growth also shows in social media engagement, with millions of interactions across YouTube, X (formerly Twitter), LinkedIn, and Facebook. Behind this rapid growth is a simple fact: large language models like ChatGPT rely on massive amounts of high-quality data. Every response or creative output it gives comes from what it has learned from that data. This is where Data Scraping plays a vital role. Data Scraping helps gather large volumes of reliable information from websites, articles, and online platforms. It collects diverse large language model data that allows AI systems to learn from real human behavior, improving accuracy and natural understanding. With efficient data scraping service...