Products, seller and consumer data mined from multiple eCommerce sites. Data includes reviews, ratings, price, product variants, SKU, categories. Additional offerings available including enriched data, advanced analytics and sentiment analysis. We are a complete e-commerce data provider offering validated and accurate product, seller, consumer review data. so that brands can make strategic decisions on product development, marketing, etc. . Our team extracts, validates, and delivers the data to meet the needs of brands based on requirements and data fields. We cover a wide range of products from the most popular e-commerce sites, including Amazon, Walmart and eBay. SetuServ offers a full range of data science and support services ranging from mining data and text analytics to dashboard development: Data Harvesting & Data Lake: Harvest data from 100+ publicly available sources and store in a standardized database to enable easy data mining and exploration Data Engineering: Standardize & automate the data processing using a data pipeline to produce reliable periodic outputs Data Mining using Machine Learning: Extract various entities such as topics, brands, eCommerce Scrapers pre-built for 100+ eCommerce sites We scrape, aggregate and organize eCommerce data across e-commerce sites, markets, and SKUs. Examples of popular sites we scrape are โ Amazon Walmart Shopee Ebay Global Coverage Our solution offers broad global market coverage with pre-built models that scrape popular eCommerce sites specific to each country. Consolidate & Translate Our solution consolidates the data into structured flat files. Once the data is consolidated, we offer translation capabilities for ease of use in large global matrix organizations. Consume in the format & frequency you like Our data can be sent to you via email as a flat file daily, weekly, monthly or a frequency of your choice. We also offer self-serve access to data pulled through our API. Automation combined with Human validation One of the key challenges with data scraping is irrelevant data associated with scraped data which can be hard to filter in later stages. Our approach combines human validation early on in key phases of data extraction and organization offering 100% noise free data.