Persuasion Analytics and Targeting
Taught by Mr. Ken Strasma

Persuasion Analytics and Targeting

taught by Ken Strasma

Aim of Course:

In this online course, “Persuasion Analytics and Targeting,” you will learn you how to apply predictive modeling methods, and persuasion (uplift) models in particular.  The focus will be on targeting voters in political campaigns. You will learn which aspects of campaigns are especially important for modeling purposes, and the difference between traditional targeting methods and more recent micro-targeting techniques. The course covers what to measure and how to design surveys to measure it.  The role of experiments is discussed, and you will learn how television advertising, online advertising, and social media fit in.

Note:  This course also serves as the lab component for certificate students in the Programming for Data Science PASS Program, who will register for it as Applied Predictive Analytics.  Students will study together in the same class, but there will be more emphasis on data for the latter students.  See also the Software section.

Anticipated Learning Outcomes:

  • Find voter targets that are appropriate to a campaign phase
  • Assess the effectiveness of a voter contact
  • Designing a survey instrument for use in a predictive model
  • Implement predictive models with voter data
  • Add uplift modeling to predict whether a voter responds better with a "treatment"
    • Conduct an A-B test
    • Include test or no-test indicator as a predictor
This course may be taken individually (one-off) or as part of a certificate program.
Course Program:

WEEK 1:  Background and basic campaign concepts

  • Why campaigns need to target
  • Phases of a campaign
  • Finding the right targets for the right phase
  • Calculating the effectiveness of a voter contact


WEEK 2: Traditional targeting vs. individual level modeling and beginning the modeling process

  • Traditional targeting
  • Microtargeting - shifting the focus to the individual
  • Deciding what to predict
  • Survey instrument design
  • The modeling process


WEEK 3: The modeling process in detail

  • Common pitfalls
  • Missing values
  • Building new indicators
  • Evaluating models
  • Combining models


WEEK 4: Persuasion (uplift) modeling

  • Controlled and natural experiments
  • Combining A-B test with predictive modeling
    • Persuasion:  determining for whom the message works
  • Targeting for broadcast television
  • Targeting for online advertising

Persuasion Analytics and Targeting

Who Should Take This Course:
Data analysts who are familiar with predictive modeling and want to learn persuasion modeling, and how to apply it and predictive modeling in general, especially in the political world.  Political consultants and staff who have had some exposure to predictive modeling, and want to dive deeper and learn how it is applied in a political campaign.
Predictive Analytics 1 or equivalent familiarity with predictive modeling methods.
Organization of the Course:

This course takes place online at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Options for Credit and Recognition:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
  1. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. Certificate - You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. CEUs and/or proof of completion - You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course,  CEU's and a record of course completion will be issued by The Institute, upon request.
  4. Digital Badge - Courses evaluated by the American Council on Education have a digital badge available for successful completion of the course.  
  5. Other options - Specializations, INFORMS CAP recognition, and academic (college) credit are available for some courses
College credit:
Persuasion Analytics and Targeting has been evaluated by the American Council on Education (ACE) and is recommended for the in the upper division baccalaureate degree category, 3 semester hours in computer science, or data mining. Note: The decision to accept specific credit recommendations is up to each institution. More info here.
Course Text:
All materials will be provided during the course.

To do the exercises in the course you will need access to and some familarity with data mining software.  Software use depends on whether you signed up for Persuasion Analytics, or Applied Predictive Analytics, which is the version of the course that serves as a capstone project for students in the Programming for Data Science PASS certificate.

The data and exercises for Persuasion Analytics students are geared to minimize the issues with data handling, and facilitate the use of XLMiner, an Excel add-in, to allow students to focus on the statistical concepts being taught in the course.

The data and exercises for Applied Predictive Analytics students bring out the issues of data size and data handling, and require the use of R or Python.

You can choose either track once you are in the class.  If you are familiar with R and Python and want to grapple with the data issues in this course, you could select the R/Python track.  Otherwise, you should choose the XLMiner track.




February 28, 2020 to March 27, 2020 August 21, 2020 to September 18, 2020

Persuasion Analytics and Targeting


February 28, 2020 to March 27, 2020 August 21, 2020 to September 18, 2020

Course Fee: $589

Do you meet course prerequisites? What about book & software? (Click here to learn more)

We have flexible policies to transfer to another course, or withdraw if necessary (modest fee applies)

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