Today’s manufacturing R&D and innovation teams face growing pressure to uncover unmet customer needs faster, with greater accuracy, and at lower cost. But traditional Voice of the Customer (VOC) approaches can be time consuming, resource heavy, and vulnerable to human bias.
At the same time, customer feedback is everywhere, across reviews, support transcripts, sales calls, communities, and more. The signals that matter most are getting harder to spot. The result? Missed unmet needs, slower innovation cycles, and teams debating opinions instead of acting on evidence.
What if purpose-built AI, guided by real VOC expertise, could help teams see more in their customer data, faster and with greater confidence?
Join Kristyn Corrigan of Applied Marketing Science (AMS) for a candid look at how manufacturers are discovering deep, solution-agnostic customer needs in unsuspected places to guide smarter product and service innovation.
What You’ll Learn:
Turn Raw Customer Input into Strategic Insight
See how a VOC optimized LLM identifies rich, hidden customer needs to reveal opportunities for true differentiation, not just broad themes or ideas you’ve heard before.
Accelerate Innovation with AI-Augmented Decision-Making
Discover how combining AI with expert interpretation leads to faster, more confident decisions and greater product-market fit.
See It in Action: Case Data and Real Examples
Review three manufacturing case studies, including what the analysis looks like and how teams translated the findings into measurable innovation impact.
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