With the rapid adoption and wide availability of traditional large language models (LLMs) such as ChatGPT, one may wonder: Why not use public AI tools for market research? While these platforms have impressive capabilities, and are useful in certain contexts, they often fall short when it comes to the nuance and depth required for rigorous Voice of the Customer (VOC) market research.
Traditional AI models yield overly generic customer insights.
While traditional LLMs can help find answers to simple questions and conduct simple research queries, they are trained on general Internet data and are not built for VOC analysis. Research shows that ChatGPT and similar AI platforms return overly generic, high-level needs. These models can’t consistently extract meaningful, actionable customer needs due to lack of industry-specific context, and therefore lack the critical, insightful details that drive successful innovation.
Traditional AI models are prone to hallucinating.
Additionally, these public AI platforms are prone to hallucinations, instances where a model generates false or misleading information (for example, extrapolating data that lies beyond its knowledge or falling prey to assumptions in the absence of complete datasets). This can be dangerous as it can introduce ideas and needs into your findings that customers did not actually share.
Proprietary data becomes public when you use public AI platforms.
Uploading your organization’s proprietary internal data to public AI platforms not only poses a significant security risk, but it can also compromise your competitive advantage.
Effective VOC studies don't just analyze customer feedback: they provide well-formulated customer needs that organizations can act upon. This requires a deep understanding of the specific industry, contextual awareness, empathy, and creativity—and, very importantly, the ability to keep internal data private. That's why we built our own supervised, finetuned LLM: one that's tailored, secure, and designed specifically to handle the complexity of VOC research.
The supervised, finetuned LLM reimagines the role of AI in uncovering customer insights. Surfacing unmet customer pain points and niche needs that are elusive to the competition is key for organizations to gain an advantage in constantly evolving marketplaces. This groundbreaking AI model has fundamentally changed how researchers can extract customer needs statements, going beyond pattern recognition to reveal even the most latent needs with precision—meaning that, when it comes to insights, organizations no longer have to choose between speed and quality.
Connect with one of our AI experts to discuss how AMS's supervised, finetuned LLM can take your VOC efforts to the next level.
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