Learn How Data Science in Digital Marketing Looks Like

According to researchers from MIT, “companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors.” 

But how does the knowledge of Data Science help Digital Marketers in their everyday duties? What is the role of Data Science in Digital Marketing? 

In this article, we will discuss What is the meaning of Data Science, the role of a Data Scientist, and how data science can be used by digital marketers to plan their digital marketing strategy in order to increase sales and profits.

Bonus Read: How Small & Medium Businesses should plan digital marketing Strategies

Firstly, let’s take a look at the specifics of the two roles and try to understand how they can complement each other to improve a business’s bottom line. 

So, without any further ado, let’s get started. 

What is Data Science and What Do Data Scientists Do?

In simple terms, Data Science is the use of algorithms, techniques, and systems to extract knowledge and actionable insights from huge amounts of structural and unstructured data. 

The key role of a professional Data Scientist’s can differ depending upon the company they work for and the industry they are working in. Some of the daily tasks and responsibilities of a data scientist are –

• Defining, extracting, and cleaning data sets
• Creating machine algorithms to implement automation tools
• Analyzing data to understand patterns and trends.
• Creating visualizations or dashboards to reflect data visually
• Researching to identify opportunities for increasing efficiency
• Predict future trends
• Presenting findings to the company to help them in decision making

Generally, these tasks can be separated into four fundamental components 

• Building and managing database
• Analyzing data
• Understanding data
• Communicating data

Data Scientists go through large amounts of data that is collected and assemble key sets based on the goals of the company or the desired metrics required by their organization. They try to understand what the data says and then communicate it to the decision-makers of their company.