Optimizing Web-Scraping Costs for a Marketing Firm
Overview: A large marketing firm asked AltheonAI to reduce their data acquisition costs associated with traditional web scraping services, freeing up capital for more innovative priorities.
Academia:
In academic research, the focus is shifting away from static traditional web scraping to AI-enhanced methods using machine learning. Studies concentrate on applying ML algorithms for pattern recognition and predictive analytics in web data— anticipating the change of web page layouts before they even happen to update data web scrapers.
Problem:
Time-consuming method impacting marketing team productivity
High costs of using conventional web-scraping services
Complexity and user-unfriendliness of existing web-scraping tools
Real World Application :
AltheonAI scoured various academic papers and developed an innovative web-scraping algorithm that beats all other existing public web-scraping services.
Impact:
Reduced the teams data acquisition costs by 99%
Saved over $100k annually, freeing up capital to be spent on other high growth projects
