Through this project, we helped a leading U.S. tire retailer monitor nationwide pricing and shipping data from 20 major competitors, covering over 50,000 SKUs and generating roughly one million pricing rows per weekly crawl. The challenges included add-to-cart pricing, login-required sites, captchas, and multi-seller listings, all of which required adaptive algorithms, caching, and contextual parsing to ensure 99% accuracy. Our QA framework, built around cached validation and

At Ficstar, we use a mix of three things to get the highest possible web data accuracy. We use NLP, plus some smart statistics, and finally, human checks to make sure everything is right. By combining the speed of machines with the careful eye of people, we make sure every piece of data is reliable. I`m going to walk you through the key steps of our process. These are the same steps we use to help our clients keep track of prices and stay competitive online.

Why Reliable Data Defines the Next Era of Pricing Strategy As CEO of   Ficstar , I spend a lot of time talking to pricing managers who rely on   enterprise web scraping   to stay competitive. And over the years, one thing has become very clear:   pricing managers are under more pressure than ever before. Margins are thin. Competitors are moving faster. Consumers are more price-sensitive. And executives are demanding answers that are backed by hard numbers, not gut feelings. I