Web Data Collection in 2022 – Everything you need to know

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Web data in 2022
Noah Kalson
Noah Kalson | Director of Brand Marketing
28-Jan-2022

In this article we will discuss:

What is web data collection?

Any information that is publicly available on the internet can be collected, and utilized to establish a dataset. These pieces of information are then used to answer business questions, power algorithms, and compete with other businesses. 

For example a new startup in the field of Customer Relationship Management (CRM) may want to collect web data telling them:

  • Which other companies are operating in their field, say by collecting information on LinkedIn, for example. 
  • What ads are being served target audiences on various platforms, say paid search results in Google
  • As well as what public sentiment is in the industry on social media 

Continuing with this example, this company may discover a considerable market gap, and need for a CRM that integrates directly with eCommerce marketplace dashboards enabling them to develop this feature, and capture increased market share. 

What do businesses try to accomplish with web data collection?

Visiting target sites and retrieving target data points (which may also be referred to as web scraping). Examples of data points include:

  • Customer reviews on eCommerce websites in order to identify new market opportunities.
  • Scanning platforms like Instagram in order to map, and identify influencers companies can collaborate with in order to set up marketing collaborations
  • Investment houses/Venture Capitalists that want to identify businesses that have certain flaws, can be turned around, and then sold for a profit following this ‘value-add’ approach
  • Human Resource departments/agencies that want to discover candidates with unique skill sets 

Who collects web data, and how is it used?  

Everyone from universities for research to data scientists for Artificial Intelligence (AI), and Machine Learning (ML). A good example of the former are academics working with the Institute of Labor to identify employment trends amongst women, and minorities. Their goals may include mapping employment journeys in order to promote workplace diversity, and integration of underrepresented populations in the workplace. 

An example of algorithmic applications of web data are investment houses that monitor news stories, social sentiment, and stock movement/volume in order to make real-time portfolio decisions such as buy, and sell orders. 

The next section will discuss the most popular applications of web data collection, and analysis by for-profit companies.

Which sectors are collecting data? 

Over the course of 2020 the following industries were leaders in terms of data-driven decision making with:

  • 65% of respondents in the banking sector reporting that they utilized data for strategic decision-making over the course of that fiscal year

While professionals in:

  • Insurance put that figure at 55%
  • Telecom came in just behind at 54%

Data-driven decision-making in organizations worldwide as of 2020, by sector

Source: Statista

According to a Business Intelligence Market Study, going into 2022 the top sectors that plan on increasing investment by 50% in Business Intelligence based on data include:

  • Retail / Wholesale 
  • Financial services 
  • Technology organizations 

Here are some examples of how businesses are using data:

  • Perform market research in order to identify market gaps/opportunities, hone Unique sale propositions (USPs), undercut the competition, and penetrate new markets   
  • Test their websites ensuring a uniform/positive experience no matter the geolocation of a given user. 
  • Monitor Search Engine Results Pages (SERPs) in order to identify organic trends that can be capitalized on as well as consumer patterns that campaigns can be tailored to. 
  • Gain a competitive advantage through pricing, and offers that change based on market activity. 
  • Carry out brand protection ensuring that no Intellectual Property is sold or utilized without consent. 
  • Verify that advertisements are not compromised, reaching intended target audiences with the correct copy, and visuals  

Methods of web data collection

Data is collected using the following three methods:

Method 1: Research-based / qualitative data collection

This includes companies that want to take a more hands-on, personalized approach in order to get more intimate with target audiences, employees, and key industry actors. Qualitative data is typically obtained through:

  • Surveys
  • Interviews
  • Search trends 

Google Search Trends Example – Source: Google

Method 2: Data collection tools (quantitative data collection)

Data Collection tools are built by companies like Bright Data. These solutions are based on complex, global networks of real-peer devices which enable companies to get an accurate picture of their target audience, and competitors. But instead of having to build, and maintain these systems in-house businesses either:

One: Plug and play

Plug into an automated Data Collector that can be customized to business needs. This creates a steady flow of information to algorithms, and team members. What is nice about this option is that you don’t need to deal with any code and all data is delivered in a format that is already structured, cleaned, and synthesized for immediate implementation. 

Two: Ready-to-use Datasets

Purchase pre-collected Datasets enabling companies to save money, and time by sharing the cost of access with other enterprises. What is nice about this option is that Datasets can be refreshed periodically, and Dataset purchases can be one-offs, quarterly or annual (so in a word they offer complete budgetary, and operational flexibility, and agility). Businesses can decide between different Dataset scopes:

  • A complete Dataset containing all the data points currently available on a specific website
  • A smart data subset consisting of a specific filter for example, all product pricing for an item between January, and February 2022
  • Differential Datasets meaning these are ‘dynamic’ in the sense that they are constantly being updated with new information. Say job titles of target individuals for a headhunting agency.
  • Merged/Enriched Datasets i.e. a complete data trove of information collected across multiple target sites giving a wider view of a given business question or challenge. For example, social sentiment regarding a certain stock or product across four different social media platforms (Reddit, Facebook, Instagram, Twitter).

Why use data collection tools (pros, and cons)?

Businesses that attempt to collect web data independently, typically find that: 

  • Manual data collection is a very time-consuming, and tedious endeavor which requires a large amount of resources be diverted away from core business operations. 
  • Target site structures, and data sets can very often change in real-time leading to some undesirable negative business outcomes. For example, ‘old’ consumer sentiment data that is utilized as part of a company’s marketing strategy can have the opposite desired effect as moods shift. 

Many companies opt to use data collection tools as they:

  • Can help to fully automate the data collection process 
  • Remove the need for companies to develop, and maintain in-house data collection infrastructure such as cloud servers, networks, Application Programming Interfaces (APIs), 
  • Enable you to divert the attention of engineers, DevOps, and IT personnel to the development of core product features
  • Provide companies with data sets that are already ‘cleaned’ (e.g. corrupted/duplicate files have been removed) , ‘structured’, and ready to be used by temas and algorithms 
  • Offer more complete, and ‘enriched’ data sets meaning information is cross-referenced and ‘bulked up’ from multiple data sources  

Why do more businesses use data collection tools?

According to Finance Online the top benefits of web data collection, and analytics include:

  1. Improved efficiency and productivity: This is largely because data creates a crucial feedback loop for organizations. For example, a company that operates in the ad tech space can use web data in order to automatically verify ad copy, link placement, and images ensuring the right ads reach the right customers, with the correct message. This makes manual checking superfluous optimizing results.
  2. Faster, more effective decision-making: Real-time web data collection enables companies to make crucial in the moment decisions. For example, an investment firm may be collecting investment data such as stock volume or social sentiment in order to make better buy/sell decisions.  
  3. Better financial performance: Companies are able to increase profitability based on a wide range of activities. One web data-driven example is being able to ‘own’ a target audience’s buying journey by analyzing web traffic, keyword, and search engine trends. Ultimately enabling better product, and brand placement, as well as more targeted lead generation.
  4. Identification and creation of new product and service revenue: By performing data-driven market research companies are able to improve their bottom line. For example, a company that maps out their competitive landscape may be able to identify a consumer need that is not being met based on consumer review/feedback data. 
  5. Improved customer experiences: Businesses can utilize web data in order to perform website, and user experience testing. So for example, companies can collect ad, content display, and third-party data based on different user geolocation, ensuring that codes, sites, ads, and web applications perform as intended. 
  6. Competitive advantage: Web data enables companies to gain a competitive edge by being able to compare live pricing and bundle offers. A good example of this is in the travel sector where Online Travel Agencies (OTAs) utilize data collection to inform their real-time dynamic pricing strategy enabling them to undercut the competition. 

Web data collection and analytics ranked in descending order of most beneficial outcomes by industry professionals 

Source: Finance Online

Why do businesses choose Bright Data for web data collection?

Or Lenchner the CEO of Bright Data often says: “The internet is the world’s largest database – the only issue is organizing its data” 

This is exactly why businesses choose to use Bright Data’s data collection solutions. Not only does it help access, organize, and prepare target datasets for immediate usage, Bright Data tools are also based on the industry-leading ethical data collection practices. This last point is crucial for businesses that want to build data-driven companies.

The top-5 reasons why businesses choose Bright Data:

Reason #1: Reliability 

The data companies can access through Bright Data tools is of the highest quality. Data is collected via a network of millions of peers that enable businesses to get accurate information based on geolocation, as it is currently being viewed by local consumers. 

Reason #2: Flexibility 

Bright Data takes customization to the next level, enabling businesses to tailor collection frequency (real-time or scheduled), output file types (JSON, CSV, HTML, or XSLS) as well as enabling scaling operations up or down at the click of a button. 

Reason #3: Compliance

Bright Data’s Know Your Customer (KYC) process is extremely rigorous employing:

  • Real-time compliance – Our compliance team receives immediate feedback, and alerts when data collection network traffic is not aligned with a customer’s declared use case. 
  • User validation –  External security companies work to review and approve all source IPs that are being given access to our data collection networks. 
  • Due diligence – New customer onboarding includes a video identity verification process which utilizes 27 internally developed KYC indicators.
  • Code-based response mechanisms – All attempts to abuse Bright Data networks are automatically blocked by code-based mechanisms.

Reason #4: Efficiency 

With Bright Dats’s collection network your company can  build higher, and grow faster leveraging existing technologies.   

Reason #5: Top-line customer experience 

A dedicated account manager is assigned to every customer. Our user-friendly dashboard gives a real time overview of all your data collection activities. Our developers release new features daily to ensure that you are using the most cutting-edge tools in order to help meet your data collection goals.  

Noah Kalson
Noah Kalson | Director of Brand Marketing

Noah oversees the brand marketing strategy at Bright Data ensuring that all marketing initiatives reflect the brand's core values. Noah has a strong background in organic marketing which helped him develop a holistic approach to marketing, branding and communication.