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Cancellation Policy: If you cancel your registration two weeks or more before the course is scheduled to begin, you are entitled to receive your choice of either a credit for a future seminar (which can be applied toward any of our courses) or a refund of the registration fee (minus a processing fee of $50). 

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 3-Day Livestream Seminar Taught by Jeffrey Dotson, Ph.D.

Transforming Traditional Methods with Artificial Intelligence

This seminar explores how to integrate Google’s Gemini AI tools into marketing research workflows to dramatically enhance analytical capabilities and research efficiency. It provides practical frameworks for AI-enhanced qualitative analysis, intelligent survey design, and synthetic respondent generation while maintaining methodological rigor and ethical standards.

The course teaches you how to use Gemini AI in three core marketing research applications:

• Advanced qualitative data analysis and automated coding.
• Intelligent survey design with AI-assisted optimization.
• Synthetic respondent generation and validation.

This seminar is designed to give marketing research professionals all the tools needed to start implementing Gemini-powered research methodologies immediately. You will gain foundational understanding of prompt engineering with Gemini, learn systematic approaches to Python-based AI integration through Google Colab, and develop practical skills for transforming traditional research workflows (no prior experience with Python is required).

The course includes hands-on exercises using real datasets and live demonstrations in both Gemini’s web interface and Google Colab notebooks. By working through these applications, you will gain the ability to process qualitative data at scale, design more effective surveys, and supplement traditional sampling with AI-generated respondents.

The course begins with comprehensive qualitative data analysis using Gemini’s advanced language processing capabilities. You’ll learn to systematically process interview transcripts, focus group discussions, open-ended survey responses, and social media content. We cover automated coding techniques, thematic analysis frameworks, and sentiment assessment approaches that maintain analytical rigor while dramatically reducing processing time.

A significant portion of the seminar focuses on AI-assisted survey design methodology using Gemini’s generative capabilities. You’ll master intelligent questionnaire development, response option optimization, question flow enhancement, and bias detection. We explore systematic approaches to creating survey instruments that leverage Gemini for cultural adaptation, readability assessment, and validity optimization across diverse market contexts.

The course provides detailed instruction on synthetic respondent generation as a methodological breakthrough for market research. You’ll learn to create AI-generated respondents that reflect specific demographic, psychographic, and behavioral profiles. We cover validation techniques, sample integration strategies, and ethical considerations for combining synthetic and authentic respondent data to enhance research scope and reduce costs.

Throughout the course, you’ll work with Google Colab notebooks that integrate Gemini’s API for scalable analysis workflows. We will address prompt engineering best practices, output validation protocols, and quality assurance techniques specific to marketing research applications.

Each day includes extensive practical exercises using Google Colab notebooks, real-world case studies from retail and B2B contexts, and interactive demonstrations of Gemini’s capabilities for marketing research applications.