Listen Labs raised $69M after a viral billboard stunt — and that’s not even the interesting part

Alfred Wahlforss was desperate. His startup, Listen Labs, needed to hire over 100 engineers, but going head-to-head with Mark Zuckerberg’s $100 million offers was a losing game. So he did something unconventional: he spent $5,000 — a fifth of his entire marketing budget — on a billboard in San Francisco that showed what looked like random numbers.

It wasn’t random. Those were AI tokens. Decode them, and you got a coding challenge: build an algorithm that acts as a digital bouncer at Berghain, the Berlin nightclub famous for rejecting almost everyone at the door. Thousands tried. 430 cracked it. Some got hired. The winner got an all-expenses-paid trip to Berlin.

That stunt went viral, and now it’s paid off in a big way. Listen Labs just announced a $69 million Series B round led by Ribbit Capital, with participation from Evantic and existing backers Sequoia Capital, Conviction, and Pear VC. The round values the company at $500 million, bringing total capital raised to $100 million. In nine months since launch, they’ve grown annualized revenue by 15x to eight figures and conducted over a million AI-powered interviews.

“When you obsess over customers, everything else follows,” Wahlforss told VentureBeat. “Teams that use Listen bring the customer into every decision, from marketing to product, and when the customer is delighted, everyone is.”

The $140 billion problem nobody wants to talk about

The market research industry is worth roughly $140 billion, but it’s built on a foundation of lies. Surveys give you “false precision,” as Wahlforss puts it. People game the system. They click the high-income bracket because that’s what they think you want. They rush through multiple-choice questions. And about 20% of responses are outright fraudulent or low-quality garbage.

“Essentially surveys give you false precision because people end up answering the same question… You can’t get the outliers. People are actually not honest on surveys,” Wahlforss explained.

One-on-one human interviews solve the honesty problem — you can ask follow-ups, probe deeper, catch inconsistencies. But they don’t scale. A single researcher can maybe talk to 30 people a week. That’s not enough to inform product decisions for a company serving millions.

Listen Labs’ approach sits in the middle. Their AI moderator conducts open-ended video conversations with participants recruited from a global network of 30 million people. The AI asks follow-up questions, probes for detail, and packages everything into executive-ready reports with themes, highlight reels, and slide decks. The whole thing happens in hours or days, not weeks.

“In a survey, you can kind of guess what you should answer, and you have four options,” Wahlforss said. “Oh, they probably want me to buy high income. Let me click on that button versus an open ended response. It just generates much more honesty.”

The dirty secret: fraud is everywhere

Building that 30-million-person panel wasn’t easy. Wahlforss called the fraud problem “one of the most shocking things that we’ve learned when we entered this industry.”

“Essentially, there’s a financial transaction involved, which means there will be bad players,” he said. “We actually had some of the largest companies, some of them have billions in revenue, send us people who claim to be kind of enterprise buyers to our platform and our system immediately detected, like, fraud, fraud, fraud, fraud, fraud.”

Listen built what they call a “quality guard” — it cross-references LinkedIn profiles with video responses, checks consistency across answers, and flags suspicious patterns. The result? “People talk three times more. They’re much more honest when they talk about sensitive topics like politics and mental health,” according to Wahlforss.

Emeritus, an online education company using Listen, reported that about 20% of their survey responses used to be fraudulent or low-quality. With Listen, that dropped to almost zero. “We did not have to replace any responses because of fraud or gibberish information,” said Gabrielli Tiburi, Assistant Manager of Customer Insights at Emeritus.

Speed matters more than you think

Microsoft is a Listen Labs customer, and their experience highlights why this matters. Traditional customer research at Microsoft could take four to six weeks to generate insights. “By the time we get to them, either the decision has been made or we lose out on the opportunity to actually influence it,” said Romani Patel, Senior Research Manager at Microsoft.

With Listen, Microsoft can get insights in days, often hours. They used the platform to collect global customer stories for their 50th anniversary celebration. That’s the kind of turnaround that makes product teams actually use research instead of ignoring it.

Other notable customers include Sweetgreen and Chubbies, both using AI interviews to build better products. The common thread is speed and depth — you don’t have to choose between statistical significance and genuine insight anymore.

What I think

I’ve been watching the AI research space for a while, and most companies in this area are trying to replace human interviewers with chatbots. That’s fine for basic market testing, but it misses the point. The real value isn’t automation — it’s the combination of scale and depth that wasn’t possible before.

Listen’s approach of using open-ended video conversations is smarter than it sounds. Video adds a layer of authenticity that text can’t match. You can see facial expressions, hear tone of voice, catch hesitation. That’s the kind of data that makes product teams actually care about research.

The $69 million raise feels justified, though I’d have liked to see more detail on retention rates and customer churn. Growing revenue 15x in nine months is impressive, but from what base? Eight figures is a wide range. Let’s see if they can maintain that trajectory as they scale.

The billboard stunt was brilliant, but it’s the product that will keep them alive. The market research industry is ripe for disruption — it’s been coasting on surveys and focus groups for decades. If Listen can deliver on the promise of fast, honest, scalable customer insights, they’ll be hard to beat.