Analyze consumer data to craft winning product strategies—no programming needed.
Students will build products that customers want and businesses cherish using real-life examples. We will study state-of-the-art qualitative and quantitative research tools, such as regression and conjoint analysis, to learn insights about our customers. We will forecast the success of a new product through modeling the size of the addressable market.
During in-class labs we will build positioning, promotional, and pricing product strategies used in the digital marketing industry today. Learn about the latest tools used to collect data, including customer research surveys, and begin data analysis using statistical and inference models. You will visualize results and create actionable recommendations.
The best part: Even though this class is data-driven, there is no programming required.
This class meets in real time in a classroom and via a remote learning platform via Zoom. Students may choose their preferred method of instruction—an in-person classroom setting or a remote format. Students are expected to attend and participate in the course, either in-person or remotely, during the days and time that are specified on the course schedule. Students who choose to attend remotely, will log into the course via Canvas at the start time of scheduled meetings and participate for the duration of each scheduled class meeting. Just like a traditional in-person class meeting, you are expected to attend and participate in the discussion. Students are also strongly encouraged to have their cameras on to get the most out of the remote learning experience.
Please have access to a computer to work through multiple hands on exercises for the duration of each scheduled class meeting.
Students attending the class in-person are expected to bring a laptop / tablet to each class meeting.
To see all meeting dates, click “Full Schedule” below.
Electronic Course Materials: You will be granted access in Canvas to your course site and course materials approximately 24 hours prior to the published start date of the course.
