If data is a fundamental part of your business model, you likely have staff capable of collecting data. But do they actually enjoy this part of the work, or would they rather focus on analysis and generating insights? Given the current tight labor market, accommodating employee preferences is strategic. This is why more and more companies are considering purchasing data rather than scraping it themselves.
Introduction
Extracting data from a webpage seems straightforward: someone with HTML knowledge builds or traditionally identifies desired elements on a webpage and saves them. This can work effectively for one-off projects or a small number of websites. However, as dependency on data grows, the process becomes less straightforward for several reasons: websites frequently change or undergo testing, browser updates occur, security issues arise, and scheduling or data processing problems can surface. Consequently, developers often rely on tools to assist with scraping.
What are the Scraping Options?
1. Build your own tooling
2. Purchase tooling
3. Outsource scraping/Purchase data
Ad. 1 Building Your Own Tooling
Choosing to build your own scraping tools typically stems from the belief that all software development should be handled in-house. This approach requires resources with specialized knowledge, experience, and constant availability to manage and troubleshoot issues. Even minor errors can lead to missing or incorrect data. Challenges here include maintaining data quality and ensuring consistent data availability.
Ad. 2 Purchasing Tooling
Scraping tools are relatively inexpensive and require minimal technical expertise to operate. However, more advanced features, such as proxy networks, demand greater knowledge. Functionality-wise, several significant drawbacks exist. Each tool utilizes a particular scraping technique, which may not be universally applicable across all websites. Additionally, as scraping tools gain popularity, they’re more easily recognized and blocked, leaving users dependent on software updates. Another considerable drawback is the frequent absence of built-in retry mechanisms in commercial tools. After scraping, errors must be manually identified, located, and re-run to maintain data quality, which is time-consuming. Finally, many available tools remain desktop-based, meaning the computer must remain operational, with scrapes manually initiated and scheduled, complicating high-volume scraping.
Ad. 3 Outsource Scraping/Purchase Data from Data partner
When scraping is outsourced, the client receives the desired data regularly. Our WSA scraping platform comprises a network of bots managed via an advanced web application. This setup allows rapid creation and efficient management of customized bots. Scheduling, error handling (including retries), and advanced proxy integration come standard. We have the expertise to employ the least intrusive scraping methods for targeted websites and servers, known as ethical scraping. Continuous monitoring and updates ensure that resources employing the latest techniques address challenges promptly. This guarantees data quality and constant availability.
Conclusion
The decision between scraping data in-house and outsourcing to a data partner depends on your required data volume, desired quality, and available employee expertise and resources. If data quality, continuity, and volume are critical to your business, outsourcing to a specialized data partner is typically the most effective solution. Collaborating with such a provider ensures accurate, reliable, and ready-to-use data tailored specifically to your business needs, guaranteeing consistent data quality, timely delivery, and reducing technical and operational complexities related to data collection and management.
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