Evolving Methods in Market Research

About this course

What you’ll learn

In this course, you will explore emerging research methods that meet the demands of today’s fast-paced, data-rich environment. You’ll examine how artificial intelligence, behavioral science, and digital technologies are transforming the way insights are gathered and used.

You’ll learn ethical best practices, strategies for integrating diverse data sources, and frameworks for evaluating and testing new tools. The course will also help you develop the skills to position yourself as a trusted advisor and help build innovation-ready organizations. Whether you’re refining your current toolkit or preparing for the next stage in your career, this course equips you to stay ahead of the curve.

• Explore the key forces driving innovation in today’s research industry.
• Understand emerging methods such as generative AI, augmented AI, neuroscience, and behavioral economics.
• Use practical frameworks to evaluate and pilot new research tools.
• Learn from real-world case studies from leading global brands.
• Navigate modern ethical, legal, and privacy requirements like GDPR and CCPA.
• Integrate attitudinal and behavioral data for deeper, more reliable insights.
• Prepare for evolving roles in insights, including prompt engineering and data translation.

Throughout the course, you’ll gain access to a curated library of 150+ high-quality resources for your self-exploration—including timely podcasts, articles, case studies, and industry publications.

Why it matters

Choosing methods that truly elevate your insights helps you cut through hype and deliver work that stakeholders trust. It sharpens your ability to make clear, confident recommendations that move projects forward. As research roles continue shifting toward strategic decision support, the skill set you will develop in this course will help you stay influential, relevant, and ready to lead.

Learning objectives

After completing this course, you should be able to:

1. Recognize the changing consumer habits that require adapted research methods.
2. Describe Artificial Intelligence as a broad subject. Demonstrate the usage capabilities of AI within market research.
3. Describe examples of behavioral economics.
4. Understand how evolutions in behavioral data (big data) can supplement market research.
5. Describe issues with synthetic responses and possible mitigation strategies.
6. Describe social listening.
7. Understand emerging data privacy considerations – data privacy best practices in market research.
8. Describe appropriate testing procedures for new market research technology and methods.
9. Assess the usefulness and efficacy of new market research methodologies.
10. Describe the role of the trusted advisor.
11. Describe the use of dashboards/data tech to unlock the full power of agile research.

Who should attend?

• Entry-level researchers looking for a general understanding of the evolving methods in the Market Research industry.
• Mid-level staff seeking to determine which evolving methodologies and approaches they could use to grow their careers.
• Experienced researchers looking to catch up with the latest developments and position their skillset for future growth.
• Corporations and supplier-side companies seeking professional development options for their internal training portfolio.
• Analysts seeking to understand how to evaluate and implement new research methods and technologies.

Continuing Education Information

Students successfully completing graded components earn a Digital Badge (Opens in a new window) and 1.2  University of Georgia Continuing Education Units (Opens in a new window) (CEUs) from The University of Georgia.

As a graduate of this course, you’ll demonstrate an understanding of how emerging research methods are shaping the industry and how to apply them responsibly in real-world contexts. This knowledge supports your credibility with peers, stakeholders, and employers by showing your ability to evaluate new tools, adapt to change, and contribute more strategically to research design and decision-making.