Adlede’s main goal is to provide a context-based solution for placement advertisements. They work with both marketing agencies and brands to help them implement contextual ad campaigns. Adlede is extracting hundreds of thousands of news articles to find the ones where it would be worthwhile to place ads. Adlede’s internal ML-based tool learns what an article is about and based on this information it matches the article with a display ad. Adlede is also developing a self-service tool that will enable its customers to build ad campaigns themselves.
One of Adlede’s main challenges is news data extraction. They need a constant influx of News data. Which is then used to fuel their internal matching tool. Without web extracted structured news data they wouldn’t be able to provide services for their clients. Before starting to use Automatic Extraction, Adlede tried to scrape the web in-house. They developed their own custom scrapers for many different websites to get the data. But over time they realized that there’s a big problem with this approach.
It took too much time and resources to maintain the scrapers. They were wasting time fixing spiders and keeping the data flow going. They found that it made more sense for them to pay for a web scraping product that can give them the data without wasting time managing the extraction code. In order to get news data from the web at scale, they needed to find a reliable and easy-to-use solution that can automatically extract data without writing any custom, website-specific code. That’s when they found Zyte API with Extraction.