eCommerce sites contain rich data, such as best sellers in each sub-category, product descriptions with key claims for each brand, and consumer opinions. Harvesting this data can yield rich insights into successful brands and the reasons for their success.
Though this data is publicly available, it’s unstructured and dispersed across various eCommerce sites. Moreover, as the products’ rank, price and reviews are updated frequently, harvesting and analyzing this data for actionable insights becomes challenging.
WebExtract is a scalable, no-code web scraper designed to extract data from eCommerce sites across the globe and seamlessly integrate data feeds into google sheets. The NLP engine of the WebExtract can analyze this data to uncover actionable insights.
To illustrate the power of WebExtract, we analyzed the 100 best sellers in the “Earbud & In-Ear Headphones” category on Amazon.com. The following are the insights from our analysis:
Top 10 brands make up ~55% of the best sellers.
The top 10 brands include a few not-so-well-known brands, such as Tozo, JLab, Otium, and CXK.
Though Apple has only seven products in the category, it has the most reviews(~30%), indicating that Apple’s products capture the lion’s market share.
In addition, though Apple products are rated marginally higher than the competitors (4.63 for Apple vs. 4.40 for Competitors), Apple’s pricing is far higher than the competitors on average ($114 for Apple vs. $40 for competitors).
Interestingly, among the 100 best-selling products, 33% are out of stock at the time of writing this blog. These “out of stock” products are spread across the brands.
Most of the 100 best-selling products have been launched over the past two years, indicating the rapid evolution of this category.
As illustrated in the above blog, eCommerce sites contain rich intelligence on the market landscape and successful brands.