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Persuasion Analytics and Targeting

Persuasion Analytics and Targeting

This course will teach you how to apply predictive modeling methods to identify persuadable individuals and to target voters in political campaigns.


In this course you will learn you how to apply predictive modeling methods with a focus on persuasion (uplift) models and how to target voters in political campaigns. You will cover which aspects of campaigns are most important, and the difference between traditional targeting and micro-targeting techniques. You will also learn what to measure, how to design appropriate surveys, the role of experiments and how to account for the impact of advertising.

Note: This course is also the lab component for students pursuing a Programming for Data Science Certificate.

  • Intermediate
  • 4 Weeks
  • Expert Instructor
  • Tuiton-Back Guarantee
  • 100% Online
  • TA Support

Learning Outcomes

In this course students will learn how to find appropriate voter targets, design survey instruments, and assess the effectiveness of voter contacts. You will implement various predictive models and testing methods to choose optimal campaign messages and media.

  • 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

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.

Our Instructors

Mr. Ken Strasma

Mr. Ken Strasma

Ken Strasma is a pioneer in the field of predictive analytics in high-stakes Presidential campaigns, serving as the National Targeting Director for President Obama’s historic 2008 campaign and for John Kerry’s 2004 presidential campaign. He produced the predictive analytics models used by the campaigns, and helped popularize the use of that technology.

Strasma is now the co-founder and CEO of HaystaqDNA, a firm that provides predictive analytics and strategic consulting services for corporations, non-profits and membership organizations.

Since 2008, Strasma has consulted on hundreds of political and corporate projects in the United States and internationally. HastaqDNA clients include multiple Fortune 500 companies with a combined market capitalization of more than $600 billion. Haystaq commercial clients span the worlds of entertainment, sports, consumer goods and healthcare. Haystaq has provided predictive analytics in international political campaigns in four continents.

Ken is the author of numerous articles and studies regarding targeting, marketing, demographics and social media analysis.

Course Syllabus

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
  • Micro-targeting – 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

Class Dates


03/08/2024 to 04/05/2024
Instructors: Mr. Ken Strasma
09/13/2024 to 10/11/2024
Instructors: Mr. Ken Strasma


03/14/2025 to 04/11/2025
Instructors: Mr. Ken Strasma
09/12/2025 to 10/10/2025
Instructors: Mr. Ken Strasma


Predictive Analytics 1 – Machine Learning Tools

This online course introduces the basic paradigm of predictive modeling: classification and prediction.
  • Skill: Intermediate
  • Credit Options: ACE, CEU
Karolis Urbonas
Susan Kamp
Stephen McAllister
Amir Aminimanizani
Elena Rose
Leonardo Nagata
Richard Jackson

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Persuasion Analytics and Targeting

Additional Information

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.

For Certificate Students
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 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.

Options for Credit and Recognition

ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for the upper-division baccalaureate/associate degree, 3 semester hours in data mining or computer science. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.

Supplemental Information

Literacy, Accessibility, and Dyslexia

At, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:







  • Navidys (for colorblindness, dyslexia, and reading difficulties)
  • HelperBird for Safari (for colorblindness, dyslexia, and reading difficulties)

Register For This Course

Persuasion Analytics and Targeting