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News articleVentureBeat AI

Listen Labs raises $69M after viral billboard hiring stunt to scale AI customer interviews

View original at venturebeat.com
VentureBeat AI - Enterprise Ai Title: Listen Labs raises $69M after viral billboard hiring stunt to scale AI customer interviews Date: 2026-01-16 14:01 Source: https://venturebeat.com/technology/listen-labs-raises-usd69m-after-viral-billboard-hiring-stunt-to-scale-ai <p>Alfred Wahlforss was running out of options…
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  • When you obsess over customers, everything else follows. Teams that use Listen bring the customer into every decision, from marketing to product, and when the customer is delighted, everyone is.

    80% confidence
  • 95% of AI pilots fail to move into production, which is why Listen Labs emphasizes quality over demos.

    80% confidence
  • Surveys give false precision because people answer the same question without nuance; you can't get outliers and people are not honest on surveys.

    80% confidence
  • Scheduling traditional focus groups with children is difficult due to school, sports, dinner, and homework; Listen Labs overcame this by fitting into children's schedules.

    80% confidence
  • Rampant fraud is endemic in the market research industry, with large companies sending fraudulent enterprise buyer profiles.

    80% confidence
  • The market research industry is approximately $140 billion annually, populated by legacy players vulnerable to disruption.

    80% confidence
  • Simple Modern went from 'Should we even have this product?' to 'How should we launch it?' after receiving rapid Listen Labs feedback.

    80% confidence
  • Listen Labs is building synthetic customer simulation to extrapolate from interview data and create simulated user voices for automated product decisions.

    80% confidence
  • Listen Labs' engineering team has 30% IOI medalists, does not train on customer data, and automatically scrubs sensitive PII.

    80% confidence
  • Listen Labs' quality guard results in participants talking three times more and being much more honest on sensitive topics like politics and mental health.

    80% confidence
  • AI-powered automated product development loops will enable companies to almost autonomously ship products by combining automated coding and automated user research.

    80% confidence
  • Emeritus did not have to replace any responses because of fraud or gibberish information when using Listen Labs.

    80% confidence
  • As something gets cheaper, you don't need less of it—you want more of it; there is infinite demand for customer understanding.

    80% confidence
  • Listen Labs removed the drudgery of research and brought the fun and joy back into research work at Microsoft.

    80% confidence
  • Traditional customer research at Microsoft could take four to six weeks, causing missed opportunities to influence decisions.

    80% confidence
  • Sling Money considers Listen Labs a total game changer, creating surveys in ten minutes and receiving same-day results.

    80% confidence
  • Listen Labs' Berghain billboard generated approximately 5 million social media views.

    80% confidence

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Late-September 2026 brought a dense run of clinical readouts: Novo Nordisk's CagriSema data at EASD, Lilly's ADtouch results for EBGLYSS, and Merck's tulisokibart Phase 2b result. Lilly's $2.9B Merida Biosciences acquisition and the 2026-11-14 FDA PDUFA date for ivonescimab sit alongside these as the main deal and regulatory events. AI-designed drugs such as rentosertib, and speculative AI-linked trial ventures such as QAIAx, are moving from hype toward clinical validation. Broader AI-sector regulatory and legal friction (Tesla Cybercab probe, xAI Minnesota ruling, OpenAI lawsuits) shows rising scrutiny that could spill into AI-driven healthcare.
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The observation date (2025-12-27) precedes Q1 2026, making it logically impossible to have actual Q1 2026 cash data at that point. Q1 2026 would not end until March 31, 2026. Additionally, the magnitude of the difference ($45.3B vs $132.42) is implausibly large even as a normal quarterly change for Apple. While different fiscal periods can show different values, the timing relationship here suggests a data integrity issue rather than legitimate period-over-period variation.
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