Digital businesses live off and thrive through data application, which is becoming even more important as the eCommerce space sees fiercer competition, with every brand trying to outdo the next brand.
Brands with more access to public data can make better decisions based on trends, customers’ reviews and comments, and other facts.
Some of the ways to make this data more available are through data mining or web scraping. These phrases may often be used interchangeably, but there is solid evidence that they are different entities.
They may serve the same purpose of making data abundantly available for brands, but they are not the same entities and processes.
Below, we will determine what these terms mean and establish the differences that exist between them.
The General Importance of Data and Its Analysis for Digital Brands
Data underlines everything from how a brand protects itself online to how it produces goods and services that satisfies customers’ wants the best.
Below are some of the importance of data in the very competitive business world:
- Brand Protection and Management
Generally, data is applied in the management and protection of a brand’s assets and reputation.
In every market and industry, brands collect large quantities of data every day to monitor customers’ reviews and feedback. Then they quickly attend to the negative ones to forestall any damage to their image and reputation.
Brands also collect data and analyze it to see if there might be some infringement on their intellectual assets.
- Market Research and Product Development
It would be impossible to understand market factors and stay on top of trends every time without putting a large amount of data to use.
Businesses collect data from various markets to determine factors such as prices, demand, supply, and even customers’ general sentiments.
Successful companies also use data to determine the next best product and the right time to produce it.
When companies use data this way, they make very few mistakes, take minimal risks, and increase their profit margin.
- Strategy Development
This is another general importance of data because every business needs a solid strategy to grow quickly and expand beyond its physical borders.
For instance, data can be collected and analyzed to create a dynamic pricing strategy that allows companies to sell their products or services at different prices at different times or to different markets.
This alone is enough to separate a striving business from a struggling establishment that finds it harder to retain customers or make sales.
What Is Web Scraping?
Data is fundamental in a business lifecycle. It inspires the best decisions and helps businesses understand the market and customers better than their competition.
One of the ways of getting this data is through web scraping. Web scraping is the process of extracting data from multiple websites and servers at once.
The extraction is usually done in large quantities; hence there is the need to use sophisticated tools for this process.
For instance, one of the most common web scraping known as C# web scraping uses a scraping tool developed with the C# programming language to interact with multiple websites and extract their content quickly.
Generally, web scraping makes data available in abundance and in real-time. The data can then be later analyzed and put into gainful application.
And lastly, the type of data extracted and how it is applied depends on the company’s needs and goals.
What Is Data Mining?
Data mining is often sometimes used to mean web scraping. While this is incorrect, it is easy to understand the confusion.
Most people wrongly use this phrase to describe a general scraping process because of a third phrase, “data extraction.” Data extraction does sound like data mining, but they are not the same thing. Data extraction is another term for web scraping, while data mining is something else entirely.
We can define the term data mining as analyzing a set of data to discover insight. It is the process that follows web scraping.
The process focuses on a set of data at a time and uses sophisticated tools that even Machine Learning to analyze to find new information. We can even say that data mining is the process of making sense out of the data gathered through web scraping.
For instance, upon scraping data from an eCommerce platform such as Amazon, you can use data mining to identify trends and understand customers’ behavior.
How is Web Scraping Different from Data Mining?
The table below shows the differences that exist between web scraping and data mining.
|Web Scraping||Data Mining|
|Used for extracting enormous amounts of data from multiple sources||Used for extensive analysis of the extracted data to make sense of it|
|Focuses mainly on data extraction||The main focus is data analysis|
|Web scraping may harvest data without knowing of its real value||Data mining shows if there is any value in large amounts of data|
|An example could be C# web scraping.
C# scraping is one of many examples of how programming languages are employed in web scraping operations
|A typical example could involve the use of mathematical models built with Python, SQL, or R|
Web scraping and data mining may sound like the same thing, but they are not. While web scraping seeks to collect large amounts of data from various data sources, data mining focuses on making sense of all the harvested data.