Homebreadcumb forward arrow iconBlogbreadcumb forward arrow iconData Sciencebreadcumb forward arrow icon5 Reasons Why Marketers should Invest in Developing Data Skills

5 Reasons Why Marketers should Invest in Developing Data Skills

Last updated:
4th Jul, 2018
Read Time
7 Mins
share image icon
In this article
Chevron in toc
View All
5 Reasons Why Marketers should Invest in Developing Data Skills

The digital and social media marketing landscape is ever-changing. It is no longer the same as it used to be in the past. While old trends must make way for the new ones, digital and social media marketers find it quite challenging to stay updated with the dynamic trends of the marketing world.

Ever since Big Data has come into the limelight, it has attracted and continues to attract entrepreneurs, marketers, and brands across the world. Today, Big Data is no less than a gold mine for marketers and companies – it is the treasure trove of hidden patterns and insights that can help find solutions to all kinds of business problems. In fact, today there is only one mantra of success in the business and marketing world – if you want to make it to the top and stay ahead in the game, data is the key!

In a study, Richard J. Vaughan analyzed the job listings in the top six metro areas for marketing, and he found that nearly 39% of marketing jobs demanded Big Data skills as a critical requirement. So, hear, hear, all the aspiring digital and social media marketers out there – it is time to embrace and develop data skills if you wish to become a part of the new digital marketing age!

Here are the data skills that every marketer should develop:

  1. Product Innovation

Brands can use Big Data tools and technology to develop and test new products while also simultaneously monitor the impact of their products on the consumers in real-time. For instance, Kraft created a strategy to involve their consumer group in their product development process actively. After monitoring and identifying two specific online trends associated with popular snacks products from consumer data- one being the requirement of portion control, and two being the concept of snacks as rewards – it released Nabisco 100-calorie packs. And within a year of launch, Nabisco raised a $100 million!

Converting Business Problems to Data Science Problems

  1. Audience Segmentation and Personalization

Harnessing Big Data, marketers can categorize their target audience into individual segments based on their tastes and preferences, behaviour patterns, age demographics, and so on. Audience segmentation will allow you to personalize and streamline communication channels (messages and emails), products and services, and marketing campaigns according to the specific needs of individual customer segments. This will not only boost customer experience and satisfaction, but it will also help you retain customers.

quick responsiveness

  1. Marketing Strategy

In the digital age powered by Big Data, there is no room for hunches anymore. Data-driven marketing strategies are the new deal now. Leveraging Big Data, companies can optimize business operations, increase sales and revenue, boost employee productivity, and so much more. As you dive into consumer data, you begin to understand their pain points and specific needs. This allows you to make accurate decisions and create data-driven marketing strategies that hold the potential to attract consumers. Today, 51% of marketing influencers depict an inclination towards data-driven decision making.

Our learners also read: Python free courses!

cmo seo
How to Make a Bright Career in Data

Explore our Popular Data Science Certifications

  1. Increase Sales and Revenue

Big Data provides accurate insights regarding what strategy or content will be ideal for each stage of the sales cycle. Not just that, Big Data analytics help boost and improve the quality of sales leads, enhance prospecting list accuracy, territory planning, and win rates for sales strategies. Today, Big Data is also helping marketers optimize product pricing through data-driven differential pricing strategies. Eventually, as sales increases, the revenue also starts showing upwards trend.
drive customer value

  1. Identify Intent Signals

It is not a hidden fact that companies monitoring intent signals through Big Data technology hold a competitive edge over their rivals in the market. Intent signals are generated through multiple data sources such as content, search queries, social media engagement, browsing behaviours, and user interaction with apps, to name a few. By tracking these metrics in real-time, you can make better business decisions. For instance, you can match your communication channels according to a particular audience segment’s stage in the buyer’s cycle. This will allow you to create excellent ad-driven sales and social media campaigns.



What Is Data Science? Who is a Data Scientist? What is Analytics?

Top Data Science Skills to Learn

upGrad’s Exclusive Data Science Webinar for you –

How upGrad helps for your Data Science Career?


While it is true that creativity is the secret sauce behind marketing and business strategies, today, it needs to be coupled with Big Data skills. Data is rapidly changing the world around us, and if you wish to keep our ideas relevant in this age, you must leverage data in creative ways. Developing the right set of data skills will help you a great deal in the long run.

Read our popular Data Science Articles

Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career.


Supriya VS

Blog Author
Supriya is managing Product marketing for UpGrad's Data Vertical. She's an engineer by education; loves learning new things, interacting with people and understanding different perspectives. She has a comprehensive experience in Marketing & Sales, Business Development and team building in a Startup venture.

Frequently Asked Questions (FAQs)

1What is the importance of Data Analytics in marketing strategies?

We are contributing to an increasingly large and varied database with every credit card transaction, each GPS pinpoint taken by our smartphone and every click we make online. This mammoth database is turned into valuable insights using Data Analytics. Over the last couple of decades, Data Analytics has revolutionized marketing by allowing brands to deliver more targeted messaging and measure their ROI. Therefore, Data Analytics is important for developing effective marketing strategies in the following ways

1. Personalized Customer Interaction : Brands are achieving improved ROI by personalizing their marketing efforts in different ways. This makes their customers feel special and valued.
2. . Greater Visibility : This tops the list of benefits of data driven marketing. Using data skills, it has become easier for marketers to track the customer’s journey from initial point of interest to final purchase of products/services.
3. Using Predictive Analytics : This can be used as the best marketing tool by the marketers to forecast consumer behaviour before it takes place. Using predictive analytics can help marketers be proactive in understanding what the customers want and will want in the near future. It also helps marketers in upselling their products, building long-term relationships with customers and determining market shifts.

2How can Data Analytics used for Digital Marketing?

The most trending digital marketing method currently is to utilise Big Data i.e. collecting massive information from various sources. This data is further processed by Data Analysts, to provide companies with helpful insights. Here are interesting ways in which data analytics augments a company’s marketing strategy:

1. Getting quality leads
2. Improving customer loyalty and retention
3. Personalization
4. Targeted dynamic ads
5. Incentive-based marketing

3What are the different types of Data Analytics Skills a data analyst should acquire?

The best Data Analytics skills a good data analyst should acquire are :

1. Communication - Communication skills include active listening, reporting, survey, teamwork, oral and written communication, conducting presentations.
2 Creativity – This skill sets include brainstorming, budgeting, collaboration, optimization, predictive modeling, strategic planning, integration.
3. Research and Critical Thinking – This mainly includes data collection, investigation, checking accuracy, process management, data interpretation, inductive reasoning, etc.
4. Data Analysis – different types of Data Analysis include Business Analysis, Cost Analysis, Predictive Analysis, Quantitative Analysis, ROI Analysis, etc

Explore Free Courses

Suggested Blogs

17 Must Read Pandas Interview Questions & Answers [For Freshers & Experienced]
Pandas is a BSD-licensed and open-source Python library offering high-performance, easy-to-use data structures, and data analysis tools. Python with P
Read More

by Rohit Sharma

04 Oct 2023

13 Interesting Data Structure Project Ideas and Topics For Beginners [2023]
In the world of computer science, data structure refers to the format that contains a collection of data values, their relationships, and the function
Read More

by Rohit Sharma

03 Oct 2023

How To Remove Excel Duplicate: Deleting Duplicates in Excel
Ever wondered how to tackle the pesky issue of duplicate data in Microsoft Excel? Well, you’re not alone! Excel has become a powerhouse tool, es
Read More

by Keerthi Shivakumar

26 Sep 2023

Python Free Online Course with Certification [2023]
Summary: In this Article, you will learn about python free online course with certification. Programming with Python: Introduction for Beginners Lea
Read More

by Rohit Sharma

20 Sep 2023

Information Retrieval System Explained: Types, Comparison & Components
An information retrieval (IR) system is a set of algorithms that facilitate the relevance of displayed documents to searched queries. In simple words,
Read More

by Rohit Sharma

19 Sep 2023

40 Scripting Interview Questions & Answers [For Freshers & Experienced]
For those of you who use any of the major operating systems regularly, you will be interacting with one of the two most critical components of an oper
Read More

by Rohit Sharma

17 Sep 2023

Best Capstone Project Ideas & Topics in 2023
Capstone projects have become a cornerstone of modern education, offering students a unique opportunity to bridge the gap between academic learning an
Read More

by Rohit Sharma

15 Sep 2023

4 Types of Data: Nominal, Ordinal, Discrete, Continuous
Summary: In this Article, you will learn about 4 Types of Data Qualitative Data Type Nominal Ordinal Quantitative Data Type Discrete Continuous R
Read More

by Rohit Sharma

14 Sep 2023

Data Science Course Eligibility Criteria: Syllabus, Skills & Subjects
Summary: In this article, you will learn in detail about Course Eligibility Demand Who is Eligible? Curriculum Subjects & Skills The Science Beh
Read More

by Rohit Sharma

14 Sep 2023

Schedule 1:1 free counsellingTalk to Career Expert
footer sticky close icon