The article explores the factors affecting data collection costs, such as data complexity, volume, frequency, and website restrictions, and outlines strategies to estimate and reduce these costs. It delves into the challenges of web scraping, including dynamic content rendered by JavaScript, the intricate Document Object Model (DOM) structures, and site-imposed restrictions like rate limiting, CAPTCHAs, and IP blocks. The article also compares in-house data collection solutions with third-party tools, discussing their respective advantages and disadvantages in terms of flexibility, control, and cost. Strategies such as proxy rotation, automation tools, and server optimization are recommended for reducing costs, while third-party solutions like Bright Data are highlighted for their efficiency in managing complex data structures and site restrictions without maintaining an in-house infrastructure. Ultimately, the article emphasizes the importance of understanding these various elements to better manage data acquisition costs and improve operational efficiency.