Business, Tech/Software

How to use data scraping to increase business information

data scraping

Image via: Pexels

This guide outlines how to use data scraping to increase business information, with 5 case studies that show the benefits.

There is a general saying today that “If it involves data, then it must involve some web scraping.” This is true because the internet contains more data than humans can collect or handle. To task a person to collect a sufficient amount of user data from the web is to allocate them with one of the most challenging jobs ever.

This is because aside from the sheer enormity of information on the internet, the process of data extraction is excruciating, tedious, and time-consuming. These are aside from the frequent errors and almost zero accuracies that accompany manual data collection.

Hence, web data scraping was invented to eliminate all of the above challenges and make harvesting data effective and efficient. Today we will see what this data scraping is, why it has become so popular, and 5 of its top use cases.

Why automated data scraping is increasingly important

Web data scraping can be defined as an automated way of using software to harvest a large amount of user data from multiple sources. The software may harvest the entire platform or stick to only a few important pages on the platform. Some of the most common sources where web data scraping is done include websites, social media platforms, and key marketplaces — even chatbot transcripts.

Web data scraping is an old concept that has only continued to evolve and become more popular and important for the following reasons:

  1. Automation

The one thing that makes web scraping so important and effective is that it automatically retrieves a large amount of data from different data sources. By using software, this once tedious and back-breaking process has become very easy, working repetitively to harvest large volumes of user data quickly.

  1. Low Maintenance

Another reason for the popularity of automated data collection is that the generally used tools require little or no maintenance at all. This means that you can consistently without worrying about maintaining the tools. If maintenance is ever required, it is usually a thing that the software developers can easily handle.

  1. Low Cost

Because it takes little time and almost zero effort on your part while requiring little or no maintenance, web scraping tends to cost companies very little as an overhead cost. Compared to the amount of data that can be harvested, automated data extraction is often seen as so cost-effective that any company, irrespective of size, can easily implement it.

  1. Data Accuracy

It is easy to think that any data is better than no data. However, the wrong or incorrect data can cause major setbacks for the brand. Hence having accurate data is very important. Automated web data scraping is coveted because of its ability to deliver very accurate user data and in real-time.

  1. Easy Implementation

All the above benefits would be hard to see if automated web scraping is not easy to implement. Using software to collect data is so easy that anyone, even those without prior knowledge, can do it.

5 examples where large scale data scraping is beneficial

Web scraping can be practically applied in any area where data is needed. However, below are 5 of the most common situations where using automated data extraction is essential:

  1. For Brand and Reputation Monitoring

For digital brands, having an irrefutable image and reputation is important. This is because it builds trust and attracts customers towards the brand instead of their competition. And the best way to maintain a stainless brand reputation is to regularly use web scraping to observe and monitor customer reviews and discussions across several platforms on the internet.

  1. For Ad Verification

Ad verification is a process that is used to monitor an ad and ensure it is performing optimally as well as prevent it from getting hijacked by internet fraudsters. Not only is ad verification essential to give the brand the best results, but it also helps to ensure that the ad does not defraud unsuspecting Internet users.

There are many methods marketers can apply to conduct ad verification; of them is using a search engine scraper. For instance, you can use SERPMaster – it automatically gathers data from Google search engine result pages, allowing advertisers to gather ad data. Please see website if you’re interested to learn more about how SERPMaster helps with ad verification.

  1. For Market Research

Market research is the process of harvesting large volumes of market data to create important market insights. This process is often required in several scenarios, including when trying to start a new business, when trying to manufacture a new product or service, or when trying to penetrate an existing market. And in most cases, the larger the amount of data collected, the better the research.

  1. For Lead Generation

Generating a list of future customers is also often achieved by running web scraping. Since buyers are often scattered across different internet spaces simultaneously, automatically collecting data from several platforms is the most efficient way to generate high-quality leads.

  1. In Real Estate

Real estate has gone beyond simply buying and selling properties as it now involves making the best investment decisions at the right time. And automated web scraping is used here to provide both buyers and sellers with the right amount of data in enough quantity to make the best decisions at every turn.

Conclusion

Data scraping is here to stay, and the only thing that may change may be the technologies surrounding it. This is mostly because it offers more advantages than anything we can presently think of.

Also, the importance of automated data collection spans several areas, including brand management, ad verification, real estate, and so much more.