Big Data and Marketing Analysis

MGT 458
Closed
Main contact
University of Toronto
Toronto, Ontario, Canada
Associate Professor, Teaching Stream
2
Timeline
  • January 10, 2021
    Experience start
  • January 26, 2021
    Proposal
  • February 13, 2021
    Data wrangling
  • March 2, 2021
    Data visualization
  • March 16, 2021
    Machine learning
  • March 30, 2021
    Final Presentations
  • April 5, 2021
    Experience end
Experience
1/5 project matches
Dates set by experience
Preferred companies
Anywhere
Any
Any industries

Experience scope

Categories
Data analysis Market research Marketing strategy
Skills
marketing strategy data analysis research machine learning python programming
Student goals and capabilities

This course aims to have students conduct marketing analytics driven by big data, using applications from real world business problems. Recent advances in computer technology have led to an explosion in the amount of data available for companies to use for market research. In order to be effective as a marketing manager today, it is necessary to understand how to apply cutting edge statistical models to large databases, such as scanner data, loyalty program data, or internet marketing data, and to be able to obtain managerial insights from model results.

Students

Students
Undergraduate
Any level
30 students
Project
60 hours per student
Students self-assign
Teams of 5
Expected outcomes and deliverables

Each group of 5-6 students (self-selected) will be completing this Big Data Analysis Project. They will work together to conduct an analysis of a Marketing case they propose, conduct analyses to be submitted in form of multiple milestones (as outlined in timeline), present their analyses in class, and prepare a final report. Examples can vary across industries, the key deliverables will be the report and a presentation thereof.

Project timeline
  • January 10, 2021
    Experience start
  • January 26, 2021
    Proposal
  • February 13, 2021
    Data wrangling
  • March 2, 2021
    Data visualization
  • March 16, 2021
    Machine learning
  • March 30, 2021
    Final Presentations
  • April 5, 2021
    Experience end

Project examples

Requirements

Students will complete applied project using Python. Concrete examples may vary depending on the industry and company-specific needs, generally the following are skills exemplified in student work:

  • Data description and analytics (Data cleaning, transformation, etc.)
  • Data visualization
  • Black box machine learning application

Additional company criteria

Companies must answer the following questions to submit a match request to this experience:

  • Q1 - Checkbox
  • Q2 - Checkbox
  • Q3 - Checkbox