Consumer research
We help your insights team get through more voice-of-customer data, faster, while your researchers stay in charge of what matters.
AI reads and structures voice-of-customer data at scale, so your team can cover far more of it than manual analysis allows.
Researchers decide what actually matters. Every finding traces back to a real quote.
Our method comes out of leading academic research by co-founders from MIT and Northwestern (Kellogg).
Team
Co-Founder & Chief Executive Officer
Julia drives the strategic vision and growth of Allemis. She holds a PhD in Management Science from MIT.
Co-Founder & Chief Technical Officer
Artem is a Professor at Kellogg School of Management. He oversees the technology powering our insights.
Product
AI-powered customer needs extraction & winnowing
Analyzing open-ended customer feedback by hand takes weeks of reading and tagging. VOC Studio does that first pass with AI, extracting, clustering, and prioritizing customer needs, so your researchers can spend their time reviewing and validating the results.
VOC Studio is built on peer-reviewed research by co-founder Artem Timoshenko: “Identifying Customer Needs from User-Generated Content”, published in Marketing Science.
AI reads unstructured voice-of-customer data and identifies the specific customer needs expressed in it. Thousands of open-ended comments become a structured list your team can review.
Related needs are grouped into themes, and redundant or non-informative comments are removed. Your researchers guide this process, so the needs that remain are the ones relevant to the decision at hand.
The result is a structured set of customer needs, each tagged by theme and scored by sentiment. Every need links back to the exact customer quote it came from, so any finding can be verified against the original review.
Contact us to request a demo or discuss a possible collaboration. Our mission is to help you create better products, services, and experiences.
Direct email — [email protected]