Coursera

Market Research and Consumer Behavior (Coursera)

Offered by IE Business School,

Your marketing quest begins here! The first course in this specialization lays the neccessary groundwork for an overall successful marketing strategy. It is separated into two sections: Market Research and Consumer Behavior. Gain the tools and techniques to translate a decision problem into a research question in the Market Research module. Learn how to design a research plan, analyze the data gathered and accurately interpret and communicate survey reports, translating the results into practical recommendations.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

You will then focus in on the consumer decision-making process, highlighting the key moments from identifying a need to buying and consuming a product. Adopt a true “consumer focus” in your managerial decisions by analyzing how consumers make decisions, what happens (in their hearts and minds) at different stages of the decision making process, and the variables that influence those decisions. This course will equip you with the knowledge required to understand the state of your product before approaching the market strategy. There’s no better place to build the foundations of your marketing journey!

Course 1 of 5 in the Marketing Strategy Specialization

Syllabus

WEEK 1
Consumer Behavioral Fundamentals
This Course consists of two blocks: Marketing Research and Consumer Behavior. First, learners will see the tools and methods to be able to effectively conduct (or hire) and interpret marketing research. Second, they will learn the foundations of consumer behavior and the consumer decision-making process and how to use this knowledge in the formulation of effective marketing strategies and tactic.
In this first module, you will head-dive into your consumer's thought-processes to really get to know what makes them tick, and, more specifically, what makes them make their purchase decisions. Getting into the mind of your customer is the first step in developing a marketing strategy that is effective.

WEEK 2
The Consumer Decision Process
Module 2 will guide you through the consumer decision-making process. Here you will explore how a potential-buyer researches a product, how they make their purchase decision, and their post-purchase evaluation. You will also understand the difference between consumer markets and business markets.

WEEK 3
Marketing Research Fundamentals
In the second half of this course, you will explore the world of marketing research. In Module 3, Professor Sinha will share with you the importance of market research and how to acquire data. Later, you will delve into the different types of experimental research and design.

WEEK 4
Marketing Research Data Collection & Analysis
In the last Module of this course, you will learn with more detail the various types of data acquired during the marketing research process and how to evaluate and assess it. Discovering the importance of, and how to create an effective survey, will also be covered.In the second half of this course, you will explore the world of marketing research.

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Coursera

Johns Hopkins University

Reproducible Research (Coursera)

Statistics & Data Analysis Data Science

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations.

Jun 1st 2026

4 Weeks

Data Analysis Data Science Reproducible Research

Coursera

Google

Process Data from Dirty to Clean (Coursera)

Statistics & Data Analysis Data Science

This is the fourth course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. In this course, you’ll continue to build your understanding of data analytics and the concepts and tools that data analysts use in their work. You’ll learn how to check and clean your data using spreadsheets and SQL as well as how to verify and report your data cleaning results. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Jun 2nd 2026

5-12 Weeks

Data Databases SQL

Coursera

Duke University

Data Visualization and Communication with Tableau (Coursera)

Statistics & Data Analysis Data Science

One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevant implications of data analyses.

Jun 1st 2026

5-12 Weeks

Excel Communication Computer Graphics

Coursera

MathWorks

Data Science Companion (Coursera)

Statistics & Data Analysis Data Science

The Data Science Companion provides an introduction to data science. You will gain a quick background in data science and core machine learning concepts, such as regression and classification. You’ll be introduced to the practical knowledge of data processing and visualization using low-code solutions, as well as an overview of the ways to integrate multiple tools effectively to solve data science problems.

Jun 5th 2026

4 Weeks

MATLAB Machine Learning Regression

Coursera

Johns Hopkins University

The Data Scientist's Toolbox (Coursera)

Statistics & Data Analysis Data Science

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

Jun 1st 2026

4 Weeks

Data Github Data Analysis

Coursera

Wesleyan University

Regression Modeling in Practice (Coursera)

Statistics & Data Analysis

This course focuses on one of the most important tools in your data analysis arsenal: regression analysis. Using either SAS or Python, you will begin with linear regression and then learn how to adapt when two variables do not present a clear linear relationship. You will examine multiple predictors of your outcome and be able to identify confounding variables, which can tell a more compelling story about your results. You will learn the assumptions underlying regression analysis, how to interpret regression coefficients, and how to use regression diagnostic plots and other tools to evaluate the quality of your regression model. Throughout the course, you will share with others the regression models you have developed and the stories they tell you.

Jun 5th 2026

4 Weeks

Python Data Analysis Linear Regression

Coursera

University of California, San Diego

Introduction to Big Data (Coursera)

Statistics & Data Analysis Data Science

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world!

Jun 1st 2026

3 Weeks

Big Data Data Analysis Hadoop

Coursera

University of Illinois at Urbana-Champaign

Digital Marketing Analytics in Practice (Coursera)

Marketing & Communication Business

Successfully marketing brands today requires a well-balanced blend of art and science. This course introduces students to the science of web analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide the foundation needed to apply data analytics to real-world challenges marketers confront daily. Students will learn to identify the web analytic tool right for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data from the web; and utilize data in decision making for agencies, organizations or clients.

Jun 1st 2026

4 Weeks

Marketing Data Analysis Digital Analytics

Coursera

Wesleyan University

Machine Learning for Data Analysis (Coursera)

Statistics & Data Analysis Data Science

Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning concepts. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering.

Jun 1st 2026

4 Weeks

Python Machine Learning Data Analysis

Coursera

University of Washington

Machine Learning Foundations: A Case Study Approach (Coursera)

Statistics & Data Analysis Data Science

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies.

Jun 1st 2026

5-12 Weeks

Python Machine Learning Clustering

Coursera

ESSEC Business School

Case studies in business analytics with ACCENTURE (Coursera)

Statistics & Data Analysis Data Science

This course is RESTRICTED TO LEARNERS ENROLLED IN Strategic Business Analytics SPECIALIZATION as a preparation to the capstone project. During the first two MOOCs, we focused on specific techniques for specific applications. Instead, with this third MOOC, we provide you with different examples to open your mind to different applications from different industries and sectors. The objective is to give you an helicopter overview on what's happening in this field. You will see how the tools presented in the two previous courses of the Specialization are used in real life projects.

Jun 1st 2026

3 Weeks

Healthcare Media Pharmaceutical

Coursera

Ludwig-Maximilians-Universität München

Advanced Competitive Strategy (Coursera)

Management & Leadership

In Advanced Competitive Strategy, we will look at how companies can build up and maintain their customer base by increasing switching costs and facilitating strategic customer lock-ins. We will find out how firms can increase their profits by pursuing suitable price discrimination and product differentiation strategies.

Jun 1st 2026

5-12 Weeks

Marketing Strategy Strategic Management