Data Analytics Basics – Introduction to Data Science For Marketeers

Data Analytics Basics – Introduction to Data Science. This part-1/session-1 of this series talks about how AI and ML are now changing the work style and methodologies of marketing. Digital marketing cannot be run as just a computerised version of the traditional market or print media. Main and exciting use cases of data science and big data analytics are exciting and make make marketing job even super exciting. Some may say it’s getting more of technology job as now its involves predicting, prescribing, planning and forecasting. Marketing work of todays time is all about problem solving and anomaly detection for business.

This post focus on marketing needs for Data Science.

Analytics: The Role Of Data In Digital Marketing
Data Revolution – Performing Analytics at The Edge
Data Science of Digital Payments

Big Data Analytics and Data Science for

  • Customer Loyalty & Retention
  • Relating to Customers
  • Online Marketing Avenues
  • Predictive, Prescriptive and Descriptive Analytics
  • Getting Quality Leads
  • Tools used for marketing Analysis

This post will support you on “How to gain deeper marketing insights through the power of data science and enable you to become a better digital marketer”. We will focus on all the pointers as mentioned above at a high level as part of the scope for this 1st Post in this series.



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Data-Driven Decisions

Understanding the importance of data and making data-driven decisions are two important factors to make digital marketing analyst job a success. Below points describe the correct order for actions needs to be taken.

  • Taking data-driven decisions is the key to successful marketing.
  • Choosing the right marketing analytics tools, measuring relevant data correctly
  • Optimizing marketing efforts with help from above 2 points.

The above efforts will make the difference between failing to reach your marketing goals and completely crushing them.

Tools like hot-jar and google analytics etc. interpret and track customer behaviour. The data out of these tools paint a beautiful picture of business insights. The insights not only help for making decisions but also able to predict and take actions on behalf.

A million dollar question “Why digital marketing analytics matter to any business” has been answered and demonstrated well by facebook and twitter etc. The golden key to success is to understand the role of big data in digital marketing.


Data Science – As A Business Capability

Data Science is making all efforts to change the perception of just being another business intelligence task. Artificial intelligence, Natural intelligence and Data Science technologies are making a huge impact on most of the business by working with big data. Demand for data science and AI-based products are rising knowingly or unknowingly. The forecast which will be a norm for sure on “Data science and AI-enabled products will be seeing the exponential market growth” will set the next style of doing business.

Current computers even with GPU don’t have the ability to process large amounts of data at once. Quantum computers for sure will have the capabilities to process an entire large enterprise database and instantly accessing all items at once. Deliver analysis and uncover patterns within seconds. 

AI and Big Data for FinTech & InsureTech
Data Intelligence as a Service – DataIntelligence

Digital Transformation of Marketing

Marketing has transformed from just print media or radio adverts to complete digital marketing business. Digital marketing without the support of big data analytics is like running a petrol car on diesel.

The digital transformation of any modern business requires quality data, not just any data. Marketing is no longer just a business or a process of creating relationships between customer and business. It’s now attaining an age where marketing is now making customers to behave one’s brand advocate. The three key success factors for any good business which helps it to grow with correct digital marketing drive are

  • Quality of Data collected.
  • Data Scientists.
  • Tools to visualise, analyse and summarise the data.

So if Data is a new fuel of today time then we must accept data scientists as oil refineries and data tools as important ingredients which help to refine and produce desired results. Cognitive Analytics provides a 360-degree view of them to make the correct decision and the right time.


Points to Note:

All credits if any remains on the original contributor only. We have covered all basics around data analytics for digital marketing analytics chapter-1. In the next upcoming chapters will talk about implementation, usage and practice experience for markets.


Books + Other readings Referred

  • Research through open internet, news portals, white papers and imparted knowledge via live conferences & lectures.
  • Lab and hands-on experience of  @AILabPage (Self-taught learners group) members.


Feedback & Further Question

Do you have any questions about AI, Machine Learning, Data Science or Big Data Analytics? Leave a question in a comment or ask via email. Will try best to answer it.


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