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:
Full-Time: (DECS-431-0 OR DECS-440-0) AND (MKTG-430-0 OR MKTGM-430-0)
E&W: (DECS-431-0 OR DECS-440-0 OR DECSM-431-0) AND (MKTG-430-0 OR MKTG-440-0)

Negative Requisites:
All Students: MKTG-953-0

Download Schedule Information

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Academic Year Term   Session Course ID Title Sec ID   Credits Syl Instructor Times Campus Location Mand 1st Exam
2020-2021 Fall 2020 10 Weeks MKTG-482-0 Customer Analytics and AI 31 1 Waisman, Caio Tue 09/19/2020-11/21/2020 8:00 AM - 11:00 AM
Tue 11/29/2020-12/04/2020 8:00 AM - 11:00 AM
Evanston TBD (Room TBA) N Remote. Learning Modalities: Entirely Remote/Synchronous
2020-2021 Fall 2020 10 Weeks MKTG-482-0 Customer Analytics and AI 81 1 Waisman, Caio Mon 09/19/2020-11/21/2020 6:00 PM - 9:00 PM
Mon 11/29/2020-12/04/2020 6:00 PM - 9:00 PM
Chicago TBD (Room TBA) N Remote. Learning Modalities: Entirely Remote/Synchronous
2020-2021 Spring 2021 10 Weeks MKTG-482-0 Customer Analytics and AI 41 1 McShane, Blake Fri 8:15 AM - 11:15 AM Evanston N/A (Room TBA) Y Please check syllabus. Learning Modalities: Entirely remote with real-time scheduled meetings. Option to attend via Zoom from a classroom in the Global Hub with other classmates (Professor will be teaching remotely). A sign-up e-form for the “Zoom Together” option will be sent to enrolled students around mid-March.
2020-2021 Spring 2021 10 Weeks MKTG-482-0 Customer Analytics and AI 41ZT 1 McShane, Blake Fri 8:15 AM - 11:15 AM Evanston Global Hub (1110) Y
2020-2021 Spring 2021 10 Weeks MKTG-482-0 Customer Analytics and AI 42 1 McShane, Blake Fri 1:30 PM - 4:30 PM Evanston N/A (Room TBA) Y
2020-2021 Spring 2021 10 Weeks MKTG-482-0 Customer Analytics and AI 81 1 McShane, Blake Sat 9:00 AM - 12:00 PM Chicago N/A (Room TBA) Y
2021-2022 Fall 2021 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
2021-2022 Fall 2021 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
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 TBD (Room TBA) Y
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 TBD (Room TBA) Y