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Web data, when extracted, refined and put to use creates new pathways to opportunity and profitability. Market research, customer acquisition, price intelligence, risk management, product development and sentiment analysis, to name a few use cases, are all powered by public web data. Businesses that tap into timely and accurate web data make informed decisions and customer insights, improve operational efficiency and increase their competitive advantage.
This probably isn’t new to you but even the most experienced business owners often overlook exploring opportunities outside of their internal data repositories. Gathering impactful web data quickly and cost-effectively using modern web scraping technology is possible. Building robust web data extraction for your organization at scale means that:
new sources of web data can be added easily,
costs of adding new sources of data can be estimated accurately, and
new business requirements and market changes can be adjusted to quickly.
You’re probably already gathering data from a handful of websites and it’s been easy so far. But as your business grows, so will your need for public web data. Don't be lulled into a false sense of security because the easy experience doesn’t translate at scale. The challenges of scaling web scraping are underestimated. Increased costs when scraping a handful of websites don’t affect your bottom line much. However, if you’re operating at scale, and extracting from 1,000 websites, those costs balloon to a much larger problem. Minimizing costs is a key feature of scaling web scraping in an effective way.
This whitepaper will walk you through what to consider when scaling your web scraping efforts from planning and design, legal compliance, crawling and extracting, artificial intelligence (AI) and quality assurance. We’ll also examine whether you should scale your web scraping operation by building in-house, taking a hybrid approach, or completely outsourcing data extraction to a third-party vendor.
Continue to the next chapter 1. A plan is a pathway to success
Web scraping enables businesses to gather public web data for market research, customer insights, and competitive advantage, enhancing decision-making and operational efficiency.
Scaling web scraping increases costs, complexity in managing data from multiple sources, and the need for robust systems to handle large-scale extraction effectively.
Scalable web scraping requires easily adding new data sources, accurate cost estimation, and adaptability to changing business needs and market conditions.
Businesses must plan for legal compliance, efficient crawling and extraction processes, AI integration, and stringent quality assurance when scaling web scraping.
Depending on resources, businesses can build in-house systems, adopt a hybrid approach, or outsource entirely to third-party vendors for efficient large-scale data extraction.
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