MKT3330 – Social Media & Marketing Analytics

Course Info

Schedule

Syllabus

  • Overview
    • Marketing has gone through several revolutions, cycling between two extremes: marketing as art and marketing as science. In today’s digital world comprised of social media, traditional digital media, and big data, marketing has evolved to become a balance of art and science. As future marketers, it is essential that you understand both. This course aims to provide you this foundation. It will be divided into two parts. The first is to help you gain an understanding of the guiding principles of how things catch on in a marketplace. The second is to help you develop some basic technical skills (programming, statistics) to become proficient at implementing and analyzing the efficacy of marketing strategies in a data world.
    • Course objectives:
      • Knowledge gained – a better understanding of why things catch on, statistical knowledge (analytical methods, shortcomings and applications), programming concepts
      • Skills gained – Python programming, Excel proficiency
  • Texts & Materials:
    • Contagious by Jonah Berger
    • Notes posted on website
    • Computing
      • A laptop with:
        • A modern PC (Windows 7 or newer) or Mac (OS X)
        • At least 2 GB hard disk space
        • At least 2 GB of RAM
      • Software:
        • Microsoft Excel (English version, Analytics Toolbox enabled)
        • Anaconda for Python 2!! (https://www.anaconda.com/download/)
          • Check the box to add anaconda to path during installation
        • Misc Python packages to be installed as the semester goes along

Analytics Group Project (Assigned 2/12/18)

Final project submission due Friday 5/11 at 12pm sharp.

  • Instructions
  • Submissions
    • Midterm (Submit a zip file of a folder containing your code and data)
    • Final (submit a zip file of your project folder w/ all code, data, and report)
    • Rate your team members by 11:59pm on 5/11.
  • Sample code

Contagious

 

Analytics Materials (posted on github)

 

  1. Stats review
    1. Notes
      1. Excel Links (helpful for your homework assignments)
        1. Excel examples, Excel formula cheatsheet
        2. Pivot table example, Video
        3. Data Analysis Toolpak in Excel
        4. Run a regression with data analysis toolpak
        5. Conditional Formatting
    2. Data
    3. Assignment
      1. Submission
      2. Resubmission (Due Noon on Wednesday 2/14)
  2. Programming with Python
    1. Notes (Download the folder)
    2. Assignment
      1. Submission (Due Noon on Monday 2/19)
      2. Resubmission (Due Noon on Weds. 3/7)
  3. Web APIs + Scraping
    1. Notes
    2. Assignment
      1. Submission
      2. Resubmission (Due Noon on Weds 3/21)
  4. Demand Modeling
    1. Notes
    2. Assignment
      1. Submission
      2. Resubmission
  5. Endogeneity
    1. Notes
    2. Assignment
      1. Submission
      2. Resubmission
  6. Discrete Outcomes
    1. Notes
      1. CBC’s Price Discrimination Segment
    2. Assignment
      1. Submission
      2. Resubmission

Labs

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