Martechvibe Features Ben Cortese’s Article on AI-Augmented Open Ends Transforming Market Research

Martechvibe, a global digital magazine and authority on marketing technology and customer experience, featured an article by KS&R Decision Sciences & Innovation Vice President Ben Cortese, PhD, on how AI-augmented open ends are transforming market research.

How AI-Augmented Open-Ends Are Transforming Market Research

At the heart of effective market research lies the ability to genuinely understand consumer sentiment, uncover hidden motivations, and explain the “why” behind decision making. Traditional quantitative research techniques often rely heavily on structured surveys with limited scope for qualitative exploration. Conversely, purely qualitative methodologies can be challenging to scale.

Enter AI-augmented open-ends — a methodology that combines the scale of quantitative research with the depth of qualitative insights, powered by AI to unlock richer, more actionable understanding.

This novel approach is not only improving data quality, but is encouraging more detailed, descriptive feedback, and in turn, enhancing the depth and actionability of insights. By utilizing AI-driven probing, researchers can dynamically generate follow-up questions and in-survey indicators based on initial responses, prompting respondents to elaborate further on their original feedback.

This poses another challenge for researchers – what do to with all of the unstructured data. Traditional open-end analysis is already a daunting task, but with AI integration, the volume, depth, and complexity of responses is even greater. Establishing an AI-assisted workflow is essential in structuring the unstructured, getting to insights quickly and without introducing unnecessary bias.

The core components driving successful adoption of AI-Augmented Open-Ends include:

• Seamless integration in the survey instrument. A pre-trained model providing probes and responses in-line with the rest of the survey drives a conversational feel, extracting valuable insights from respondents.
• Human led, AI-assisted code frame generation. Large Language Models (LLMs) are excellent at digesting and summarizing key themes from unstructured data at scale, and with human guidance, are much more efficient than traditional manual processes.
• AI-assisted open-end coding. A hybrid approach where researchers provide project-specific training data to refine LLM outputs has shown to be indistinguishable from traditional human coding.

Once this workflow is established, researchers can transform traditional processes through AI-augmented open-ends, enhancing operations and activating new applications.

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About KS&R

KS&R is a nationally recognized strategic consultancy and marketing research firm that provides clients with timely, fact-based insights and actionable solutions through industry-centered expertise. Specializing in Business Services, Telecom, Entertainment & Recreation, Healthcare, Retail & E-Commerce, Technology, and Transportation & Logistics verticals, KS&R empowers companies globally to make smarter business decisions. For more information, please visit www.ksrinc.com.