Public Policy 30510: Data Analytics for Campaigns

Winter 2014
Tuesday-Thursday 10:30-11:50
Harris 224

Contact Information:

Rayid Ghani
Office: Searle 219 (or by appointment Harris 176)
Office Hours: Harris 176 – Tuesday and Thursdays 1-2pm (or by appointment)
Email: rayid [at] uchicago [dot] edu

Course Description:

This course will teach students:

  1. Data analytics methods, tools, and infrastructure required to run successful campaigns.
  2. What role data analytics plays in advocacy and political campaigns
  3. How to structure and design campaigns analytically.

We will use examples and data from both political as well as issue based advocacy campaigns, with the focus being on campaigns that are aimed at making people take specific actions.

This course is useful for students who are interested in working in political or other types of issue based campaigns as well as students who want to learn more about how data-driven campaigns are structured and learn about data analytics methods to improve campaigns.

This is a hands-on course where students will learn to use data analytics tools to analyze data coming from campaigns. Prior familiarity with SQL, Excel, R, Python, Tableau is helpful but not required.


  • Data Analytics Tools and Methods
    1. Databases
    2. Reporting
    3. Visualization
    4. Statistical Analysis
    5. Predictive Models & Machine Learning
    6. Experiments
  • Functional Analytics: Analytical approaches to improve different functions of campaigns
    1. Fundraising
    2. Volunteer Recruiting
    3. Voter Registration (for political campaigns)
    4. Persuasion Analytics
    5. Get out the Vote Analytics (for political campaigns)
  • Channel Analytics: Analytical approaches to effectively use various communication channels
    1. Field Analytics
    2. Digital Analytics
    3. Media Analytics


The following lectures are a work in progress. The schedule is subject to change based on class interest and progress. In addition, we will have guest lectures which will cause some of these lectures to be merged. If there are additional topics you’d like to cover or guest lectures you’d like to see, please let me know.

  1. Course Overview: Goals, Expectations, Structure [Assignment Due January 12] [Data set]
  2. Role of Analytics in Obama 2012 Campaign: Overview
  3. Role of Analytics in Obama 2012 Campaign: Deeper Dive
  4. Campaigns: Creating an Analytics-driven Campaign Strategy
  5. Data Analytics 1: Databases, SQL, Tableau
  6. Data Analytics 2: R, Python
  7. Data Analytics 3: Machine Learning and Predictive Models
  8. Data Analytics 4: Designing, Running, and Analyzing Experiments
  9. Fundraising Analytics
  10. Volunteer Analytics
  11. Voter Registration Analytics
  12. Persuasion Analytics
  13. GOTV Analytics
  14. Field Analytics
  15. Digital Analytics
  16. Media Analytics
  17. Building an analytics team and organization
  18. Data Analytics Infrastructure
  19. Data Integration and Matching
  20. Getting your work used in campaigns


  • Short weekly assignments based on case studies
  • Short response to lectures due Tuesday before class

Project: Students will form groups and work on a project they’ll propose after week 3.

Resources and Readings:



  • Machine Learning
  • Experimental Methodology