Marketing Research Course

Course Description

This course provides students with both the framework and technical expertise to collect, analyze, and implement market research. They will learn the different types of data that drive marketing decisions, and learn essential skills such as exploratory research, market sampling, cross-sectional research, and building regression models.

Course Objectives

Video Transcript

Welcome to marketing research. So, I’m really happy to be working with you this semester. And let me introduce myself and the course a little bit. I’m introducing myself because that’ll kind of show you how my interests evolved, and I understood better what I should cover in a course like this. My name is Amiya Basu. I’m of Indian origin, and I’ve been here for a long, long time. I came here as an undergraduate, I did physics at the Indian Institute of Technology. I came over here to do a PhD in physics, then drifted to marketing. Eventually, I got my PhD from Stanford University a long time back. But, at that time, I was very, very quantitatively driven. Basically, the mathematical models interested me, that part of marketing. There is a lot of it in marketing. Then I went to teach at the University of Illinois, Urbana-Champaign, which is a very psychology-driven place. But there I appreciated the things that I never paid any attention to—the psychology of choice, how to make a question, what kind of biases may arise. I got a much better appreciation for that.

So, the way I teach marketing research evolved from just focusing on the statistical methodology to the types of data that we collect. And in the process of data collection—the errors that we can make very, very easily—can we fix it, into issues like that. Since 1992, I have been teaching at Syracuse University. And I teach this class as well as I teach mathematical models to PhD students. Sometimes I teach several courses on data analytics. So this class is marketing research. So marketing research, you can broadly think of it as a collection of data, analysis of data, to help improve decision-making by managers. Basically, to get a better idea of what the marketing environment is like. So there is that element of what data should we collect to begin with, how to store that data, how to organize the data. Also, how to analyze that data. So both sides, data collection and data analysis, are parts of marketing—marketing research. So marketing research, you can think of two types of marketing research. One is the big data, the types of things to do in a data business analytics type course. Lot of the time, there is data that are generated by organizations or come to organizations in a very big volume on a regular basis.

In this course, we’ll introduce you to some data like that. Like there is a database made available by the Dominick’s store chain in Chicago. Basically, the weekly sales of something like 15,000 different items, stock keeping units by that store chain through 1989 through 1997, huge data set. And I’ll use some examples drawn from that. The nice thing about the data set, it’s publicly available. But my course largely will not be on data analytics. Those items will be available. I’ll give you some, make some extra notes available to you in case you want to pursue it further. But this class would be focusing on smaller data sets, largely the types of research you do when you do a small piece of research starting from scratch.

So, the course will be basically broken up into segments. In the front part, we’ll start by discussing the types of data that we collect from customers. We’ll talk about the different ways we can proceed to collect that data, expert data research, which is largely flexible, open ended, to get a better idea, sense of what types of data that we need, so that we don’t miss out anything significant, descriptive research that is more standardized server research where we focus on the statistical data analysis. And experiments where we change something, measure the impact of that change on some outcome of interest. We’ll talk about one particular thing called attitude measurement. Basically, measuring how much somebody likes or dislikes a product and whether we can do anything about it by changing the features of the product. We’ll talk about question construction. This will be basically the front part of the course, the data collection side of the course.

Then the course would end with discussion of data analytics. But in between, there is a transition area, which is sampling. Typically, when we are talking about customers, we are interested in a specific customer population, say the students at a university, a specified population. In practice, we usually do not study the whole population, only a small part, which is called the sample. So, talk about what are the alternative sampling methods used in practice. What are the things that can go wrong? And talk about one particular method called simple random sampling, which is also the method most statistics courses focus on, and talk about how to construct confidence interval. Basically, if I estimate something, how much margin of error should we allow. And the reverse problem, that is at the sample-planning stage. If I decide the margin of error should be days, what sample size we need? So we’ll talk about that sampling. And finally, in the data analysis, we’ll talk about how we can frame simple research questions—that is hypothesis testing—that helps our decision-making and how we can answer them using statistical analysis.

The course will end with one specific method, regression analysis. So, in a course on statistics, we’ll go through many details of that. Here, I’ll keep it very, very simple. What is the meaning of the model? What do the parameters mean? And, how we can answer managers’ significant questions looking at the parameters that you estimated? So, in the presentation of the course itself, the taped lectures that you hear, I’ll just focus mostly on the theory and ideas. We’ll expand on them when we go for it in our weekly sessions. And there will also be small projects that you will be doing—both on data collection, data analysis—to supplement these discussions. So I’ll try to keep the software that you need to things that are easily available, like Excel. But, we’ll find out precisely what is available. We might use packages like Minitab, if they are available. So that is something we’ll find out as the time comes. So, welcome to the course. I’m really excited to work with you, and hope at the end of it, you like the area as much as I do. Welcome.

Course Objectives

By the end of the course, online Master of Business Administration students will be able to:

  • Identify appropriate data points and implement effective processes to collect them
  • Understand different research strategies and apply them efficiently
  • Build data models that accurately evaluate and communicate research findings
  • Implement research findings to improve marketing initiatives