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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 Research Methods with Artificial Intelligence

Marketing research faces unprecedented opportunities for transformation through artificial intelligence integration, yet most practitioners lack systematic frameworks for leveraging these powerful tools effectively. This course addresses the critical gap between traditional research methodologies and AI-enhanced approaches that can dramatically improve both efficiency and analytical depth across the research process.

Conventional marketing research methods often suffer from significant limitations including sample bias, resource constraints, subjective interpretation of qualitative data, and limited analytical sophistication in data processing. These constraints result in slower research cycles, higher costs, and potentially incomplete insights that fail to capture the complexity of contemporary consumer behavior. Furthermore, traditional approaches struggle with scale limitations and consistency challenges that become particularly acute in global research contexts.

This course introduces practical frameworks for integrating AI tools—primarily ChatGPT and related large language models—into every stage of the marketing research process. You will develop systematic approaches to AI-enhanced research design, data collection, analysis, and insight generation while maintaining methodological rigor and ethical standards. The emphasis is on practical implementation rather than technical programming, making advanced research capabilities accessible to traditional marketing research practitioners.

The course establishes foundational principles for AI integration in marketing research, addressing key considerations including prompt engineering, output validation, and bias mitigation strategies. We examine how AI tools can enhance traditional research methodologies while preserving scientific rigor and interpretive validity.

Survey design methodology is revolutionized through AI assistance, covering intelligent questionnaire development, response option generation, and survey flow optimization. We explore systematic approaches to creating survey instruments that leverage AI for question refinement, bias detection, and cultural adaptation across diverse market contexts.

Synthetic respondent generation represents a methodological breakthrough, enabling researchers to supplement traditional samples with AI-generated responses that reflect specific demographic and psychographic profiles. We examine validation techniques, ethical considerations, and integration strategies for combining synthetic and authentic respondent data.

Qualitative analysis transformation includes systematic approaches to processing in-depth interviews, focus group transcripts, open-ended survey responses, and scraped digital content. We develop frameworks for thematic analysis, sentiment assessment, and insight extraction that maintain interpretive depth while dramatically increasing analytical speed and consistency.

A/B testing enhancement through AI covers intelligent test design, automated analysis interpretation, and strategic recommendation generation. We explore how AI can identify optimal testing parameters, interpret complex interaction effects, and translate statistical findings into actionable business insights.

Conjoint analysis methodology is enhanced through AI-assisted attribute identification, scenario generation, and preference modeling interpretation. We examine systematic approaches to designing conjoint studies that leverage AI for both methodological optimization and insight synthesis.

Advanced applications include competitive intelligence gathering, social media analysis, and predictive modeling for market research applications. We address integration challenges, quality assurance protocols, and organizational implementation strategies for scaling AI-enhanced research capabilities.

At the conclusion of the course, you will:

• Master systematic frameworks for integrating AI tools into traditional marketing research methodologies while maintaining scientific rigor and ethical standards.
• Design and implement AI-enhanced surveys including intelligent questionnaire development, synthetic respondent integration, and automated quality assurance protocols.
• Transform qualitative analysis capabilities through systematic approaches to processing interviews, focus groups, and open-ended responses using AI-powered thematic analysis and insight extraction.
• Develop comprehensive research programs that leverage AI for experimental design, data analysis, and strategic storytelling while ensuring methodological validity and actionable business recommendations.