Introduction to Decision Science for Marketing from Coursera

Welcome to the Introduction to Decision Science for Marketing course! This course will introduce the principles and methods of data analytics as they apply to marketing. You will learn how and why to use data and analytics to inform marketing decisions and strategies.

This beginner-level course provides awareness about the present practice of data-driven decision-making in the marketing discipline. This will help you familiarize yourself with practical tips about when and where to use various techniques and tools. You will learn about critical theories and concepts with the help of relevant examples.

To succeed in this course, you should have basic clarity of concepts of the marketing discipline. As a prerequisite for the course, you should know key marketing terms, such as segmentation, targeting, and positioning.

After the successful completion of this course, you will have basic understanding of how to use data for making marketing predictions. You will have sufficient knowledge of foundational elements, the relationship between data and marketing constructs/concepts, and how decision science and marketing work in tandem to produce relevant insights for today’s market. Finally, the course provides concrete strategies to start with decision science in marketing.

What's inside

Syllabus

Introduction to Decision Science for Marketing

Decision science or data analytics for marketing (predictive marketing) are new approaches to customer relationships, using big data and machine learning techniques. It is a critical opportunity for marketers and is still in the early stages of adoption. In this module, you will learn why and how companies of all sizes adopt decision science. The early adopters have seen great value in it, and new technologies make it easy to implement.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Develops skills in building customer profiles, using data analytics to predict marketing outcomes, and implementing strategies for growth and retention

Taught by Prof. Lalit Pankaj, an expert in the field of decision science and marketing

Provides a practical approach to data-driven marketing

Covers essential topics including customer segmentation, predictive analytics, and personalized recommendations

May require prior knowledge of basic marketing concepts

Designed for beginners in the field of data-driven marketing

Reviews summary

Practical marketing decision science foundation

According to learners, this course offers a positive solid foundation in applying neutral decision science to marketing, making it particularly valuable for those new to data analytics in this field. It provides positive practical strategies and relevant examples for leveraging data to inform marketing decisions across the neutral customer lifecycle. While it excels at delivering a positive beginner-friendly overview, some students noted that it maintains a warning strategic focus, which might mean a warning lack of in-depth technical detail for those seeking advanced analytical methods or hands-on tool usage. Overall, it prepares marketers to think predictively and apply data-driven approaches.

Requires prior understanding of basic marketing terms.

"You definitely need basic marketing clarity before starting, as the course assumes knowledge of terms like segmentation."

"Having a grasp of key marketing concepts was crucial to follow the discussions effectively."

"I appreciated that it built on existing marketing knowledge, allowing for deeper dives into decision science."

Emphasizes strategy over deep technical implementation.

"This course is more about the 'why' and 'what' of predictive marketing, rather than the 'how-to' with specific tools."

"I was hoping for more hands-on labs or coding examples, but it remained largely conceptual."

"If you're looking for advanced machine learning models, this course only scratches the surface; it's a high-level overview."

Logical flow with regular assessments.

"The modules flowed logically, making it easy to follow the progression of topics."

"Weekly summative assessments helped reinforce learning and check my understanding."

"The course effectively covered customer lifecycle, value, and retention strategies."

Offers relevant strategies for real-world marketing.

"The practical tips and relevant examples provided made the concepts highly applicable to my work."

"I learned concrete strategies to start using decision science in my marketing efforts immediately."

"The course clearly demonstrates how data analytics informs actual marketing decisions and strategies."

Provides excellent foundational knowledge for beginners.

"As someone new to decision science in marketing, I found this course an excellent starting point."

"It really helped me grasp the core concepts of predictive marketing without getting too technical."

"I now have a basic understanding of how to use data for marketing predictions, which was my goal."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Decision Science for Marketing with these activities:

Review Statistical Analysis Concepts

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Review this course's prerequisite statistical analyses.

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Review notes from a previous statistics course.
Take a practice quiz on statistical analysis.
Watch a video tutorial on statistical analysis.

Review Decision Science for Marketing Terminology

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Decision science for marketing requires a solid foundation in marketing terminology. Review foundational concepts and jargon to ensure clarity before starting the course.

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Create a list of 10 key marketing terms.
Write a short definition for each term.
Review your list to ensure you have a clear understanding.

Practice Customer Segmentation Techniques

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Building customer profiles is a key skill in decision science for marketing.

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Find a dataset that contains customer data.
Use a data analysis tool to segment the customers into different groups.
Write a report that describes the different customer segments.

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Follow a Tutorial on Predictive Marketing Techniques

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Predictive marketing techniques are used to optimize the efficiency of marketing campaigns.

Browse courses on Data Analysis

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Find a tutorial on predictive marketing techniques.
Follow the tutorial and complete the exercises.
Write a summary of what you learned from the tutorial.

Practice Using Data Visualization Tools

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Data visualization is a key skill for marketers to master.

Browse courses on Data Visualization

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Find a dataset that you would like to visualize.
Choose a data visualization tool that you would like to use.
Create a data visualization that communicates the insights from the data.

Develop a Marketing Campaign for a New Product

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Create a marketing campaign for a new product to demonstrate how to determine the target market.

Browse courses on Marketing Campaign

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Choose a product that you would like to market.
Conduct market research to identify your target audience.
Develop a marketing campaign that is tailored to your target audience.
Write a report that outlines the steps you took to develop your campaign.

Enter a Data Analytics Competition

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Competitions are a great way to test your skills while learning decision science for marketing.

Browse courses on Data Analytics

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Find a data analytics competition that you would like to enter.
Form a team or work independently.
Develop a solution to the problem.
Submit your solution to the competition.

Career center

Learners who complete Introduction to Decision Science for Marketing will develop knowledge and skills that may be useful to these careers:

Digital Marketing Specialist

Digital Marketing Specialists typically have a background in marketing, computer science, or a related field, and usually must have a bachelor's degree at a minimum. This course can be helpful for this role, as it builds a foundation for data analysis within marketing. Understanding data analytics can help a Digital Marketing Specialist better understand consumer behavior online and make better decisions.

See salaries and explore the career path for Digital Marketing Specialist

Search Engine Optimization (SEO) Specialist

Search Engine Optimization (SEO) Specialists typically have a background in marketing, computer science, or a related field, and usually must have a bachelor's degree at a minimum. This course can be helpful for this role, as it builds a foundation for data analysis within marketing. Understanding data analytics can help a SEO Specialist better understand consumer behavior online and make better decisions.

See salaries and explore the career path for Search Engine Optimization (SEO) Specialist

Social Media Manager

Social Media Managers typically have a background in marketing, communications, or a related field, and usually must have a bachelor's degree at a minimum. This course can be helpful for this role, as it builds a foundation for data analysis within marketing. Understanding data analytics can help a Social Media Manager better understand consumer behavior online and make better decisions.

See salaries and explore the career path for Social Media Manager

Content Marketing Specialist

Content Marketing Specialists typically have a background in marketing, communications, or a related field, and usually must have a bachelor's degree at a minimum. This course can be helpful for this role, as it builds a foundation for data analysis within marketing. Understanding data analytics can help a Content Marketing Specialist better understand consumer behavior and make better decisions.

See salaries and explore the career path for Content Marketing Specialist

Email Marketing Specialist

Email Marketing Specialists typically have a background in marketing, communications, or a related field, and usually must have a bachelor's degree at a minimum. This course can be helpful for this role, as it builds a foundation for data analysis within marketing. Understanding data analytics can help an Email Marketing Specialist better understand consumer behavior and make better decisions.

See salaries and explore the career path for Email Marketing Specialist

Data Analyst

Data Analysts typically have a background in computer science, statistics, or a related field, and usually must have a bachelor's degree at a minimum. This course can be helpful for this role, as it builds a foundation for data analysis within marketing. Understanding data analytics is a fundamental skill for this role, and this course can help aspiring Data Analysts build a foundation.

See salaries and explore the career path for Data Analyst

Market Research Analyst

Market Research Analysts typically must have a bachelor's degree in marketing research, statistics, or a related field. Understanding data analytics is important for this role, and this course can help build a foundation for success. Market Research Analysts study market conditions to help companies understand consumer behavior, and data analysis can be crucial for this work.

See salaries and explore the career path for Market Research Analyst

Marketing Manager

Marketing Managers typically have a background in marketing, business, or a related field, and usually must have a bachelor's degree at a minimum. A course like this one can be very helpful for this role, as it builds a foundation for data analysis and marketing decision-making. Understanding data analytics can help a Marketing Manager better meet the needs of consumers.

See salaries and explore the career path for Marketing Manager

Product Manager

Product Managers typically have a background in engineering, marketing, or a related field, and usually must have a bachelor's degree at a minimum. This course can be helpful for this role, as it builds a foundation for data analysis within marketing. Understanding data analytics can help a Product Manager better meet the needs of consumers.

See salaries and explore the career path for Product Manager

Sales Manager

Sales Managers typically have a background in sales or a related field, and usually must have a bachelor's degree at a minimum. A course like this one can be very helpful for this role, as it builds a foundation for data analysis and marketing decision-making. Understanding data analytics can help a Sales Manager better meet the needs of consumers and make better decisions.

See salaries and explore the career path for Sales Manager

Business Analyst

Business Analysts typically have a background in business, computer science, or a related field, and usually must have a bachelor's degree at a minimum. This course can be helpful for this role, as it builds a foundation for data analysis within marketing. Understanding data analytics can help a Business Analyst better understand consumer behavior and make better recommendations.

See salaries and explore the career path for Business Analyst

Marketing Consultant

Marketing Consultants typically have a background in marketing, business, or a related field, and usually must have a bachelor's degree at a minimum. This course can be helpful for this role, as it builds a foundation for data analysis and marketing decision-making. Understanding data analytics can help a Marketing Consultant better meet the needs of clients and make better recommendations.

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Affiliate Marketing Manager

Affiliate Marketing Managers typically have a background in marketing, business, or a related field, and usually must have a bachelor's degree at a minimum. A course like this one may be helpful for this role, as it builds a foundation for data analysis and marketing decision-making. Understanding data analytics can help an Affiliate Marketing Manager better understand consumer behavior and make better decisions.

See salaries and explore the career path for Affiliate Marketing Manager

Customer Success Manager

Customer Success Managers typically have a background in sales, marketing, or a related field, and usually must have a bachelor's degree at a minimum. This course may be helpful for this role, as it builds a foundation for data analysis within marketing. Understanding data analytics can help a Customer Success Manager better understand customer needs and make better recommendations.

See salaries and explore the career path for Customer Success Manager

User Experience (UX) Researcher

User Experience (UX) Researchers typically have a background in psychology, human-computer interaction, or a related field, and usually must have a bachelor's degree at a minimum. This course may be helpful for this role, as it builds a foundation for data analysis within marketing. Understanding data analytics can help a UX Researcher better understand user behavior and make better recommendations.

See salaries and explore the career path for User Experience (UX) Researcher