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Role of data science professionals in marketing

Data Science

When you launch a new product or service, your first priority is to spread the word about it as a market. Since the completion is super high and has already reached the upper limit, the task won’t be easy. In fact, you will face maximum challenges in popularizing your product or service.

This is where the concept of marketing comes into play. It is a broad and comprehensive subject that covers various techniques and technologies that are used for spreading the word about a certain product, service, or brand. In other words, marketing means promoting your business and its elements in a way that you can get more sales and revenues.

In earlier days, people used traditional marketing methods such as printing pamphlets, making announcements, relying on references, and so on. However, these have become obsolete because the current market is super competitive, and if you do not adopt new and innovative technologies, your business will soon fall out of the race. 

That’s why most businesses now invest in learning the role of data science in marketing. The following article will walk you through the importance of using data science in marketing techniques and the results yielded from them.

Importance of data science in marketing

Data science is a process through which hidden information sets are extracted from any kind of data and then converted into visual insights through graphs and charts. Visualization is important because no one will be able to understand raw data or the unstructured information extracted from it through processing.

Once the insights are obtained, the use of data science in marketing can be easily acknowledged. Following are some of the pointers that will help you understand how this new technology has helped marketers to take their practices up by several notches. 

  1. Data science helps in understanding the market in depth with the help of real-time insights. For example, you can easily know how the market trends are shifting or which practices have become obsolete using a comparative analysis. As a result, you won’t be investing in obsolete practices or techniques which might cause more harm than good.
  1. It is very important for every marketer to understand what the target audience is expecting. Long gone are the days when businesses used to rely on their practices only. Nowadays, every business needs to focus on what the target audience wants and expects if they want to gain success. This is why investing in data science is important because it allows businesses to know what the target audience wants, their expectations based on demographics, and many other factors.
  1. With the help of data science in marketing, professionals can know the expected risks or chances or failure in the business. For example, when you want to roll out a new product or service, you can use visual studies from data science to check if it will be accepted well by your target audience or not. If the studies do not yield appropriate results, you can plan a new strategy for rolling out the concerned service or product in the market. So, it is evident that with the help of data science, you can mitigate the risks and failures to a great extent.
  1. As we have already discussed, data is very powerful at this time. If you use it appropriately and analyze the data sets to reveal the hidden information, you will be able to make data-driven decisions. For example, you can decide whether your business requires an improvised marketing funnel or not according to the response you have received from your target audience over the past 6 months. The decision will be taken upon the real-time results from data analysis and not based on assumptions.
  1. Last but not least, data science in marketing has a crucial role in optimizing the overall budget of the business. As the risks of failure will be reduced, you won’t have to spend a lot in mitigating them at every step. 

Besides, you can target the right section of the audience and drive maximum sales for your business. So, data science will not only increase the incoming revenues for your business but also reduce the money invested in risks, failures, and so on.

You may like to know the application of data science across sectors.

Marketing areas where data science plays a key role

Although data science in marketing can be used in several ways and implemented in multiple areas, it is better to understand the key roles of this new concept. In other words, one should learn how data science is implemented in marketing, along with its benefits.

  1. Data-driven marketing

One of the important ways in which data science can be used is through implementing data-driven marketing. This method allows marketers to rely on the information obtained from real-time data and make important marketing decisions. 

For example, studying the competitors will help your business to learn if the target audience you decided for the new product or service is right or not. If the target audience isn’t able to drive sales for your business, it would be better to look for another section that meets your requirements.

So, here the marketing decisions will depend upon the real-time insights obtained from data, thereby helping you implement data-driven marketing in your business. 

  1. Predictive modelling

Another way in which data science can be used in marketing is through predictive modelling. It is a process where you use an advanced analytical model based on artificial intelligence and machine learning to predict a certain outcome or scenario. 

For example, when you want to decide if you must reduce product prices or provide discounts, predictive modelling will be of great help. 

You use the existing data sets and study the patterns and trends to earn a prediction on the plants you have made. If the predictions are in your favor, you can go on and reduce the prices or offer discounts.

  1. Marketing analytics

From the name itself, you can understand that marketing analytics is a process through which raw data can be converted into valuable insights through data processing and visualization. 

For example, you can convert feedback and surveys into visual insights through graphs and charts to understand how many people are in favor of a new upgraded product version. If the number is significantly high, launching the new version will earn you success and vice versa.

  1. Customer segmentation

This marketing practice has impacted the marketing through data science positively. It is a concept where a huge customer base is segregated into multiple blocks, where each block will have a common set of characteristics. 

For example, my new target is a kids’ market for new clothes. You can use customer segmentation to divide the market into several blocks. One block can represent kids who usually like to wear casual clothes, and the other one represents children who always want to dress in fashionable ways. 

Challenges and limitations of data science in marketing

Data securityimplementation of top notch security practices such as passwords, double layer authentication system, and so on
Lack of skillsmarketers need to adopt new skills to deal with the changing dynamics of data science in marketing
Inaccuracydata science models need to be passed on machine learning and artificial intelligence to reduce the accuracy and precision issues in the results


Data is a storehouse of information that, when extracted, can reveal many secrets of the market, target audience, customers, and several other business pillars. So, investing in data science in marketing can yield valuable insights and help businesses overcome roadblocks and achieve success. 

If you want to become a successful marketer, enroll in online M.Sc. in Data Science or online MBA in Data Science from Manipal Academy of Higher Education (MAHE) at Online Manipal. It will help you sharpen your skills and develop a competitive advantage. 

Key takeaways: 

  • Data reveals information about the business, market, customers, and target audience to allow professionals to make real-time decisions.
  • From marketing analytics to predictive modelling, data science in marketing can be used in various ways.
  • The challenges in implementing data science in marketing involve security issues, skill gaps, and so on.


Information related to companies and external organizations is based on secondary research or the opinion of individual authors and must not be interpreted as the official information shared by the concerned organization.

Additionally, information like fee, eligibility, scholarships, finance options etc. on offerings and programs listed on Online Manipal may change as per the discretion of respective universities so please refer to the respective program page for latest information. Any information provided in blogs is not binding and cannot be taken as final.

  • TAGS
  • data science
  • Marketing
  • Online MSC Data Science

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