Course Detail

Digital and Algorithmic Marketing (37304)

Course Description by Faculty

  • Misra, Sanjog
  • Content
    Marketing in the digital economy requires strategic and tactical decisions to be made with a high level of precision, at a more granular level and quicker than ever before. It should come as no surprise then that decisions in various marketing functions (including advertising, promotions, pricing and even product design) are now made based on or with the help of data and analytic algorithms. One could say that these algorithms are the marketer’s new competitive toolkit.

    In this class we will explore the use of such algorithmic tools in furthering a firm’s digital (and non-digital) marketing goals. In particular, we will focus on methods to capture a consumer’s digital footprint and the algorithms used to use this data to tailor, improve and optimize the firm’s marketing investments. This course will require students to be conversant with digital technologies and somewhat comfortable with data and analytics although expertise is not required.

    In addition to classroom discussions the course will feature speakers from firms engaged in algorithmic and digital marketing as well as project(s) that apply tools learnt in class to real problems.

    • Lectures

    • Discussion

    • Case Studies

    • Group Projects

  • Prerequisites
    This course has two strict prerequisites - 37000 (Marketing Strategy) and either 41000 or 41100 (Statistics). The course can be taken concurrently with the pre-requisite courses. In some rare circumstances, the prerequisites can be waived entirely, but only when I am convinced the student has extensive knowledge of the material covered in one of the courses.

    In addition, to the above students will also benefit from having completed other marketing courses (Pricing, Data Driven Marketing) and other courses at Booth that deal with data and computing (e.g. Big Data). These are, however, not required.

    The course is somewhat computationally intensive and makes extensive use of R. Some familiarity with R (or programming in general) is essential to extracting full value from the course. Students should take a self-assessment (which will be made available at least a month before bidding commences) to ascertain their familiarity with the basic elements of R before enrolling.
    • Strict Prerequisite

  • Materials
    • Canvas Site Available

  • Grades
    No pass/fail grades. No auditors.
    • Graded homework assignments

    • Graded attendance/participation

    Assessment & Testing
    • Final exam (in class)

    • No auditors

    • No pass/fail grades

  • Syllabus
  • Winter 2023Section: 37304-01TH 8:30AM-11:30AMHarper Center3B - Seminar RoomIn-Person Only
Description and/or course criteria last updated: June 8 2022