The ultimate guide to automated web scraping solutions

Companies know they need web data in order to better compete, and resonate with target consumers. They also know that web scraping is an extremely resource-heavy, and time-consuming endeavor. This guide offers an automated alternative for companies that want the best of both worlds.
The ultimate guide to automated web scraping solutions
Nadav Roiter - Bright Data content manager and writer
Nadav Roiter | Data Collection Expert

In this article we will discuss:

What is web scraping? 

In a nutshell, web scraping is the act of collecting target data from websites. It can be accomplished either manually or in a more automated process involving a ‘bot’ or ‘web crawler’. The act of scraping entails identifying the open-source data that is of interest, copying it, and then storing it in a database and/or spreadsheet so that it can then be used by algorithms and teams in order to make important business decisions.

What you can accomplish with web scraping?

Web scraping enables you to find the target data you need, and to subsequently parse, search, and format the information to be used later on by a database. Here are some examples of common data points collected by businesses through web scraping as well as what they enable those businesses to achieve:

  • Competitive/Pricing data – When trying to compete in a field such as eCommerce, businesses want to know how their competition is approaching consumers in real-time. They will therefore utilize web scraping to gain access to competitor pricing, listing copy, conversion rates, best-selling items in their niche, bundle offers, and the like. This helps them understand buyer engagement, telling them what does/does not work so that they can grab increased market share. 
  • People/business data – When looking to map out an industry either for investment, human resources/recruitment, or industry analysis purposes, businesses will scrape sites like LinkedIn, and Crunchbase. It is in this way that they can understand how well funded a given entity is, how many employees they have, if they are growing, what their Unique Sales Proposition (USP) is, as well as what unique skill sets potential recruits may have. 
  • Investment data – Hedge funds, Venture Capitalists, and portfolio managers utilize web scraping as a tool to understand where industries are headed, and how they can best position themselves for revenue, success, and growth. They look to see which companies have the biggest opportunity for value-add by identifying potential markets, and audiences that are untapped at present. This may present itself as data that highlights high audience engagement coupled with low conversion rates, for example. Additionally, companies may use web scraping to identify securities that are currently undervalued, and ripe for investment. This might present itself in the form of data, such as lower than usual stock trading volume coupled with strong company financials, and positive investor sentiment on forums, and discussion groups. 
  • Social media data – Entities looking to tap into social media data may want to collect information that helps them identify key industry players otherwise known as ‘influencers’. This information may help with marketing campaigns, collaborations, and brand positioning. Companies may also be looking to identify consumer sentiment regarding certain products or services, as well as user engagement with certain types of relevant content. This can help them create buyer-driven production and marketing strategies that in turn gain more traction, and drive sales. 

How does Data Collector help with web scraping automation? 

Companies involved in web scraping know two things:

  1. Gaining access to target data is a powerful tool that enables them to compete better, and resonate with consumer groups. 
  2. Web scraping is a massive undertaking that is very resource-heavy. It requires dedicated groups of engineers, IT, and DevOps professionals that need to work to unblock target data, as well as clean, synthesize and prepare data for use by algorithms. They know that web scraping requires building, and maintaining hardware, and software such as servers in order to be able to identify, collect, and analyze data which will provide them with a unique informational advantage in their industry. 

It is for these reasons that companies are turning to automated data collection solutions that serve as a viable alternative to traditional web scraping. One of the most effective tools in this context is Data Collector, which helps optimize, and streamline the data collection process in the following ways:

  • It offers a zero-infrastructure approach, shifting the manpower, and infrastructure maintenance to a third party. 
  • It takes care of all coding and unblocking efforts by creating real-time workarounds to site architecture changes. 
  • It cleans, matches, synthesizes, processes, and structures the unstructured website data before delivery so that algorithms and teams can ingest data, decreasing the time from collection to insight. 
  • It enables levels of scalability that are in line with what modern, industry-leading companies need. Allowing teams to turn on and off data collection operations on a per-project basis. 
  • It gives businesses more control over the collection and delivery schedule, be it a target data point that needs to be collected/refreshed on an hourly/daily/monthly/yearly basis. It also delivers those data points in JSON, CSV, HTML, or Microsoft Excel. Sending information to the location which is most comfortable for a particular company or team to consume it, including webhook, email, Amazon S3, Google Cloud, Microsoft Azure, SFTP, and API options. 

The bottom line 

Businesses can use web scraping to get in touch with their customers and figure out who else is in their field, which helps them make their goods and services more appealing. Data gives businesses the feedback loop they need to act in the real world instead of operating under assumed or imagined circumstances. Web scraping, on the other hand, can be time-consuming and costly, which is why businesses that want to grow quickly are increasingly turning to web scraping automation. They outsource their data collection so they can focus on honing their craft, focusing on what they love and are good at, and setting the tone in their fields.

Nadav Roiter - Bright Data content manager and writer
Nadav Roiter | Data Collection Expert

Nadav Roiter is a data collection expert at Bright Data. Formerly the Marketing Manager at Subivi eCommerce CRM and Head of Digital Content at Novarize audience intelligence, he now dedicates his time to bringing businesses closer to their goals through the collection of big data.