Knowing What Your Customers Want, All the Time: Listen Labs' Alfred Wahlforss
In a Nutshell
Listen Labs is an AI platform that runs thousands of voice interviews simultaneously to replace slow, biased traditional market research with fast, traceable customer insights. It builds detailed audience profiles across 30 million participants, enables targeted research on niche segments like high-value Sweetgreen customers, and validates findings against real sales data. The company's simulation feature lets companies predict customer responses without new interviews, positioning AI-driven strategy as the next bottleneck after execution becomes automated.
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Listen Labs' goal is to reach a billion people in their audience and stratify them to identify what each person is an expert on. Even niche topics like sneakers have influencers and early adopters whose insights are significantly more valuable. The platform builds profiles of people across interviews, enabling targeted searches to find the right participants.
Alfred Wahlforss is the founder and CEO of Listen Labs, an AI-first customer research platform that can run thousands of voice interviews simultaneously. The company launched about a year ago and now serves 20% of the Fortune 500, including Microsoft, Anthropic, Sweetgreen, and NBC.
Listen Labs has an AI agent that understands customers better than companies can by talking to them directly. The process works as follows: a user asks a question like "how can you improve course onboarding," and Listen creates an interview guide with instructions for the agent. Using an audience of 30 million participants, the platform can find virtually anyone—from oncologists to software engineers—and conduct hundreds of interviews. The system then analyzes the data and provides recommendations. A simulation feature launching in a couple of months will allow companies to predict how customers will answer future questions after tens of thousands of interviews have been completed.
As we get closer to AGI, it will be easier to build things, but the hard part will be knowing what to build.
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