THE NEED OF DATA SCIENCE IN TODAY’S MARKETING

THE NEED OF DATA SCIENCE IN TODAY’S MARKETING

It won’t be a lie to say that the need for data science in today’s marketing world has become more than ever.

Due to the affordability of the World Wide Web, online information has drastically shot up. Almost every single day, around 2.5 million terabytes of data are generated which is no less than a gold mine for marketers. If it is properly dug up, it can deliver valuable insights that can be used to target potential customers. In other words, concealing within the mounds of online data is the knowledge that could empower the marketers and encourage them to strategize more intellectually.

However, decoding huge chunks of data is an arduous task and that is where Data Science can play its part.

Before diving deeper into the importance of data science in today’s competitive marketing world, let’s understand what exactly data science is.

DATA SCIENCE

The straightforward definition of data science is the practice of extracting meaningful information or discovering hidden patterns from the big raw data. The image below summarizes the data science process in the easiest way.
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 Data Science is the new oil to your Marketing Strategy Engine:

As a marketer, how about if you could discern the precise requirements of your customers from their past browsing history, purchase history, buying patterns and income, etc.

Wouldn’t it be amazing as it will help you in efficiently optimizing your marketing strategies and derive maximum revenue?

Definitely, it would be as you will be in a better position to communicating the value of your organization’s product or service to the targeted customers as compared to your competitors.

Need for Data Science in Marketing:

In the 21st century, many companies are optimizing their marketing campaigns and tactfully handling various business operations with the help of data science. As it has enabled them to foretell demands and events; develop a deep understanding of consumer behavior, intent, and browsing habits.

Let’s look into a few marketing strategies where data science can be implemented to produce outstanding results.

1. Formulation of a Proper Social Media Engagement Strategy:

Social Media is one of the finest platforms to gather important data about businesses’ new and existing customers.  Although there are countless social media sites, Facebook, LinkedIn, Instagram, and Twitter have the most active users around the world. Therefore, these sites have a circulation of immense user-generated content that can assist companies with marketing research, communication, and relationship development.

Marketers often rely on that user-generated content and use data science to identify which leads are exploring the particular social media page, what content the customer clicked on, and more. With these right insights, marketers formulate a proper social media engagement strategy.

2. Identifying the Right Channels

As day by day, social media sites are becoming great in number, it has become important to understand which specific channel is delivering the proper return to the business. Here, data science can play its role by determining which channels are giving ample lift for the marketer. Using a time series model, a marketing data scientist can compare and recognize the kinds of lift seen in different channels. This can prove highly beneficial as it tells the marketer exactly where:

  • To deliver relevant and valuable content to attract customers.
  •  To place the paid ads to get more ROI.

3.  Budget Optimization for Marketing Campaigns

Organizations allocate a specific budget to the marketing department therefore they are always under a strict budget. The ultimate aim of every marketer is to derive maximum ROI from their allocated budgets. However, this is not as simple as it sounds. Achieving the defined target within the resource constraint is always tricky and time-consuming. Things don’t always go according to plan due to unforeseen events and efficient budget utilization is not accomplished.

By interpreting a marketer’s spend and acquisition data, data science can help to build a spending model that can aid in utilizing the budget better. The model can help to distribute the budget across locations, channels, mediums, and campaigns to optimize key metrics.

Conclusion:

Considering the above- mentioned practical ways where data science can be implemented in marketing, one can easily perceive that understanding data science techniques can be marketers’ new best friend to keep their shareholders and customers happier.  

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