Dr. Ksenia Polson

Dr. Ksenia Polson

Assistant Professor

Marketing and Data Sciences

Anderson College of Business and Computing

303.458.4138
3333 Regis Blvd, Denver, CO 80221
Ph.D.

About

Dr. Ksenia Polson serves as an Assistant Professor in the Marketing and Data Sciences Department in the Anderson College of Business and Computing at Regis University. Her expertise spans the intersection of marketing analytics, consumer behavior, and data science methodologies, bringing both theoretical depth and practical application to her teaching and research.

Dr. Polson's research interests focus on data-driven marketing strategies, consumer analytics, and the application of advanced statistical methods to understand market dynamics and consumer decision-making processes. She is particularly interested in how modern data science techniques can enhance marketing effectiveness and provide deeper insights into consumer behavior patterns.

As an educator, Dr. Polson is passionate about preparing students for the evolving landscape of data-driven business decisions. She combines rigorous academic training with practical skills development, ensuring her students are well-equipped to tackle real-world challenges in marketing analytics and data science. Her approach emphasizes both technical proficiency and strategic thinking.

Areas of Expertise

Marketing Analytics & Strategy

Specialized in leveraging data analytics to drive marketing strategy and measure campaign effectiveness, with focus on ROI optimization and customer acquisition strategies.

Digital marketing analytics
Campaign performance measurement
Marketing attribution modeling

Consumer Behavior Analytics

Expert in analyzing consumer decision-making patterns, purchase behavior, and customer journey mapping using advanced data science and statistical methodologies.

Customer journey analysis
Behavioral segmentation
Purchase prediction modeling

Statistical Analysis & Research Methods

Proficient in advanced statistical methods and research design for business applications, with emphasis on experimental design and causal inference in marketing contexts.

Experimental design and A/B testing
Multivariate statistical analysis
Survey research methodology

Data Science for Business

Expertise in applying data science techniques to business problems, with focus on predictive modeling, machine learning applications, and data visualization for insights.

Predictive modeling and forecasting
Customer analytics and segmentation
Business intelligence and visualization