Data extraction - helping businesses see the bigger picture

Now, planning an effective marketing strategy that succeeds totally depends on what data you extract and use to derive insights.
Getting targeted information that helps you take informed decisions about your business is what matters.

As a result, the trend of treating data as a science has emerged. 'Data scientist' is a term you might not have heard of a few years down the line. Today, however, it is suddenly a trending term and many data scientist positions have been generated across companies and across industries.

Why? Because, marketing professionals understand and want to leverage the benefits of data and derive business insights.

What Is data scraping and what sources are probed to excavate the desired information?

Data can be collected from both internal and external sources. Internal sources like invoices, claims, sales records etc and external resources like websites, social media, from survey polls, data bases etc. Experts use several... web scraping & data Extraction API and also carry out data extraction into Excel files. This data is then structured, analysed and specific patterns are unveiled, thus helping decision makers gain insight.

Some specific uses of data extraction include:

• Extracting the pricing of products similar to your product - to decide the best and most highly competitive price for your product.
• Extraction of leads from online business directories.
• Add-on product for payroll data extraction to define improvement opportunities and enhance efficient management.
• Gather information about customers, who buy a particular type of product to aptly determine your market segment and plan product pitching strategies.
• Extract data regarding what keywords are used the most in order to search for a particular product, this gives you an idea of what keywords to use while pitching your product.
• Extracting customer sentiments about service or product for planning new product launch or introducing new schemes.
• Extraction of sales information to analyse seasonal sales pattern for introducing seasonal offers.

Big data challenge and the rise of data scientist:

As massive volumes of data were generated via various modes and mediums and due to increased use of mobile devices, the big data threat was introduced. To counter this, the need for a specialist who could separate the useful from the non-useful information and further structure the unstructured useful data to uncover patterns, and help businesses see the bigger picture and gain answers to specific questions; arose.

Armed with analytical tools, data scientists discover patterns from the extracted data. As mentioned above these patterns are analysed and the derived insights are used to make informed decisions that help boost sales, garner a wider customer base, and hence drive business towards growth.