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Customer Analytics and AI (MKTG-482-0)
1.00 Credit
TCE BidStats

Description:
Marketing is evolving from an art to a science. Many firms have extensive information about consumers' choices and how they react to marketing campaigns, but few firms have the expertise to intelligently act on such information. In this course, students will learn the scientific approach to marketing with hands-on use of technologies such as databases, analytics, machine learning, and computing systems to collect, analyze, and act on customer information. While students will employ quantitative methods in the course, the goal is not to produce experts in statistics; rather, students will gain the competency to interact with and manage a marketing analytics and AI team. We will use the statistics program R in Customer Analytics and AI. R is harder to use that Stata but has become the industry standard (together with Python) and is extremely good for data management, visualization, and Machine Learning. Before you start the course, you will need to learn how to use R using tutorials and online course. There will be an assignment that is due at the beginning of the first class to make sure that you are sufficiently proficient in R before the course starts. Please do not take this class if you are not willing or able to make this investment. The course consists of lectures, in-class exercises, group work, and case discussions. You will use R throughout the class to work with individual-level customer data. The course has no final; instead, students are evaluated on their performance on weekly assignments. This course has no overlap with other existing analytics or AI courses at Kellogg. The course is an excellent companion to Retail Analytics.

Prerequisites:
All Students: (DECS-431-0 OR DECS-435-0 OR DECS-440-0 OR DECSM-431-0) AND (MKTG-430-0 OR MKTGM-430-0)

Negative Requisites:
All Students: MKTG-953-0

Download Schedule Information

Command item
  
Academic Year Term   Session Course ID Title Sec ID   Credits Syl Instructor Times Campus Location Mand 1st Exam
2021-2022 Fall 2021 10 Weeks MKTG-482-0 Customer Analytics and AI 51 1 Waisman, Caio Fri 09/20/2021-11/20/2021 1:30 PM - 4:30 PM
Fri 11/29/2021-12/04/2021 1:30 PM - 4:30 PM
Evanston Global Hub (1110) Y Confirm with professor and syllabus.
2021-2022 Fall 2021 10 Weeks MKTG-482-0 Customer Analytics and AI 81 1 Waisman, Caio Thu 09/20/2021-11/20/2021 6:30 PM - 9:30 PM
Thu 11/29/2021-12/04/2021 6:30 PM - 9:30 PM
Online N/A (Room TBA) Y Confirm with professor and syllabus.
2021-2022 Spring 2022 10 Weeks MKTG-482-0 Customer Analytics and AI 41 1 McShane, Blake Fri 8:30 AM - 11:30 AM Evanston Global Hub (2410 A&B) Y Confirm with professor and syllabus.
2021-2022 Spring 2022 10 Weeks MKTG-482-0 Customer Analytics and AI 42 1 McShane, Blake Fri 1:30 PM - 4:30 PM Evanston Global Hub (L130) Y Confirm with professor and syllabus.
2022-2023 Fall 2022 10 Weeks MKTG-482-0 Customer Analytics and AI 31 1 Waisman, Caio Fri 1:30 PM - 4:30 PM Evanston TBD (Room TBA) Y
2022-2023 Fall 2022 10 Weeks MKTG-482-0 Customer Analytics and AI 81 1 Waisman, Caio Thu 6:00 PM - 9:00 PM Chicago TBD (Room TBA) Y
2022-2023 Spring 2023 10 Weeks MKTG-482-0 Customer Analytics and AI 31 1 McShane, Blake Tue 1:30 PM - 4:30 PM Evanston TBD (Room TBA) Y
2022-2023 Spring 2023 10 Weeks MKTG-482-0 Customer Analytics and AI 32 1 Zettelmeyer, Florian Mon/Thu 10:30 AM - 12:00 PM Evanston TBD (Room TBA) Y
2022-2023 Spring 2023 10 Weeks MKTG-482-0 Customer Analytics and AI 41 1 Zettelmeyer, Florian Mon/Thu 8:30 AM - 10:00 AM Evanston TBD (Room TBA) Y
2022-2023 Spring 2023 10 Weeks MKTG-482-0 Customer Analytics and AI 81 1 McShane, Blake Tue 6:00 PM - 9:00 PM Chicago TBD (Room TBA) Y