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“Fields of gold”: Scraping web data for decision-making insights

Sponsored Feature Presented by Bright Data
Erez Naveh VP Products at Bright Data - Business Express
Erez Naveh, VP Products, Bright Data

By Erez Naveh, VP Products, Bright Data

The days of doing business in the traditional way are long gone. Meetings to source information, on the ground research, sifting through mountains of data to arrive at the same conclusion, gone! Today, businesses are smarter, tapping into technologies that allow them to go further than before, changing the way they operate.

Recognising that data can now be collected and used to create newer processes, products, and even applications, means that organisations are now fully relying heavily on data to guide them into their future success. As such, data is now the path towards innovation, and rightly so given the amount of it available freely. But, how does it get collected and where from?

Web scraping allows businesses to gather actionable insights, in real time, deep down into the markets they serve for their customers. To put it simply, this is the process of gathering web data from a variety of internet sources, whether it is product information, price, SERP (Search Engine Results Pages) data, or customer sentiment data from various global marketplaces. Many of these businesses rely on web data providers to deliver tools that can collect data on demand.

The tools used for web scraping range from no-code web scrapers (i.e., tools developed to gather web data from certain websites) to data gathering infrastructure designed to handle the blocking strategies of numerous websites. When an IP address visits the same URL too frequently, websites frequently use blocking techniques like CAPTCHA or return erroneous web data. This is despite the fact that these websites are entirely public domain, which means that anyone with a regular internet connection can freely access them.

By avoiding the aforementioned difficulties, these online scraping solutions help with the data collection process and give companies without a strong data collection department the chance to compete on an equal footing with much larger industry players. Businesses can acquire the same insights that industry leaders have been using for years by implementing such user-friendly technologies.

What are data sets then?

Data sets are large sets of data or information that focus on a single subject collected from either single or various other sources. These sets are then structured into readable tables or formats from which valuable insights can be easily drawn.

There are alternatives to the online scraping methods that many businesses use to independently gather live public data. For instance, some businesses specialise in gathering and structuring ready-made data sets that may be used or purchased right away. As a result, businesses can still use data without spending the time and money necessary to gather it. These partners, who offer the entire range of services and deliver data on demand, are available for businesses to purchase public web data sets directly. There is a data set for every industry, whether it be for e-commerce, banking, stock market trading, or human resources.

What about the “public” element to data sets?

Public data sets, similar to data sets, are large sets of structured web data that businesses use to create static collections of information to answer important operational questions. This could include public information, such as company information, directories, search engine results, e-commerce web data, financial and stock market data, public social media web data, and so on and so forth.

Web Scraping vs. Data sets?

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Web scraping is used by companies that need to collect data in real time. One prime example is in e-commerce, where companies typically change their strategies by the hour. Such a strategy might be employing dynamic pricing, where companies will collect web data on similar competitor products as the hours go by, not only looking at pricing but also at consumer sentiment and product details. This information helps them change their product strategies in real time in accordance with the market, helping to maximise their exposure as well as increase profit margins.

Data sets are more static collections of public data, meaning that they are updated periodically, as opposed to in real time. Data sets can be more beneficial than web scraping when seeking the following four elements:

  • Coverage: Data sets are more comprehensive. They include entire records and data from target websites, such as all products from Walmart, all the jobs listed on Indeed, or all the companies on Crunchbase.
  • Quality: Both methods should be quality focused. When it comes to data sets, web data vendors monitor the collection of the web data to ensure the completeness of the data set. From there, the provider can monitor and refresh the data at sufficient intervals.
  • Enrichment: Many public web data providers include enrichment options in their original services. They can add information on top of the data collected from the websites to create more value.
  • Operational efficiency: Buying data sets, as opposed to collecting them using web scraping techniques, does not require any data collection infrastructure or in-house development team to collect and parse data, thereby saving time, effort, and money.

Data sets are becoming a practical choice for businesses who simply want to put their data collecting on autopilot, even though they are not updated in real time.

How businesses make use of data sets?

Data sets are used by companies to gather insights and discover emerging trends in the market. Web data, and public web data sets, allow companies to paint a complete picture of the markets they serve, as opposed to a sectioned-off portion of a particular market.

For example, retailers are able to deploy pricing models that can react to the ebb and flow of the market, discover new inventory or opportunities, monitor MAP pricing efforts, and better position their products, whether monetarily or through new messaging, to attract a larger audience and maximise profit margins. Additionally, financial institutions use public data sets to project the valuation of their investments more accurately. Whether it be product details to estimate profitability, company information, or a company’s ESG objectives, using public data sets helps financial institutions better compare and understand their future and current investments.

Human resource managers are another example; they can leverage public data sets to greatly enhance processes tied to recruitment, development, performance, and compensation. They do this by pulling web data from websites such as LinkedIn, Indeed, Glassdoor and Crunchbase which helps them peer into the looking glass of how workers seek employment and how organisations can attract and retain employees.

The right tools can do the right jobBright Data Logo Copy Copy - Business Express

If companies cannot heavily invest in resources to perform in-house web data scraping and analysis, or the emphasis is on more comprehensive data and not necessarily on the “freshness” of the data – data sets may be the suitable path forward. These companies simply need to turn to third-party data providers to purchase ready-made tools, infrastructure as well as public data sets to enrich their data storage, improve their decision-making process, and set their organisations on the right path for success.

Using the tools provided by the public data provider or purchasing data sets directly from them saves companies countless hours of collecting data in-house. It also saves them money that would otherwise be spent on developing teams and infrastructure as well as even more time implementing these strategies from end to end.

Overall, web data providers are providing businesses with new cost-effective options to perform fast and reliable public web data collection at scale. These web data providers are also allowing smaller players to compete alongside the market frontrunners by enabling them to access and analyse the same information as everyone else and draw their own insights.

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