Alfred Wahlforss was running out of options. You can’t get the outliers. Of like, automated decision making overall can be bad, but we will have considerable guardrails to make sure that the companies are always in the loop.”The company already handles sensitive data with care. The platform replaces the traditional choice between quantitative surveys — which provide statistical precision but miss nuance—and qualitative interviews, which deliver depth but cannot scale.Wahlforss explained the limitation of existing approaches: “Essentially surveys give you false precision because people end up answering the same question… “Write code is now getting automated. Decoded, they led to a coding challenge: build an algorithm to act as a digital bouncer at Berghain, the Berlin nightclub famous for rejecting nearly everyone at the door. “In a survey, you can kind of guess what you should answer, and you have four options,” Wahlforss said. With Listen, they reduced this to almost zero. 430 cracked it. So he spent $5,000 — a fifth of his marketing budget — on a billboard in San Francisco displaying what looked like gibberish: five strings of random numbers.The numbers were actually artificial intelligence tokens. “Obviously, as you said, there’s kind of ethical concerns there. They’re much more honest when they talk about sensitive topics like politics and mental health.”Emeritus, an online education company that uses Listen, reported that approximately 20% of survey responses previously fell into the fraudulent or low-quality category. Within days, thousands attempted the puzzle. Wahlforss invoked the Jevons paradox, an economic principle that occurs when technological advancements make a resource more efficient to use, but increased efficiency leads to increased overall consumption rather than decreased consumption.”What I’ve noticed is that as something gets cheaper, you don’t need less of it. Microsoft used Listen Labs to collect global customer stories for its 50th anniversary celebration. The round values Listen Labs at $500 million and brings its total capital to $100 million. The process took about an hour to write questions, an hour to launch the study, and 2.5 hours to receive feedback from 120 people across the country. Traditional customer study at Microsoft could take four to six weeks to generate insights. But building that panel required confronting what Wahlforss called “one of the most shocking things that we’ve learned when we entered this industry”—rampant fraud.”Essentially, there’s a financial transaction involved, which means there will be bad players,” he explained. “There’s infinite demand for customer understanding. “Why we’re replacing them is that one, they’re super costly. It reflected the intensity of the talent war in the Bay Area.”We had to do these things because some of our, like early employees, joined the company before we had a working toilet,” he said. But Listen Labs is betting that in the artificial intelligence era, the companies that listen fastest will be the ones that win. In nine months since launch, the company has grown annualized revenue by 15x to eight figures and conducted over one million artificial intelligence-powered interviews.”When you obsess over customers, everything else follows,” Wahlforss said in an interview with VentureBeat. “Oh, they probably want me to buy high income. The only question is whether customers will talk back. “We went from ‘Should we even have this product?’ to ‘How should we launch it?'” said Chris Hoyle, the company’s Chief Marketing Officer.Chubbies, the shorts brand, achieved a 24x increase in youth study participation—growing from 5 to 120 participants — by using Listen to overcome the scheduling challenges of traditional focus groups with children. The result, according to Wahlforss: “People talk three times more. And I understand that there were issues in the liner of the shorts and that they were, like, scratchy, quote, unquote, according to the people interviewed.” The redesigned product became “a blockbuster hit.”The Jevons paradox explains why cheaper study creates more demand, not lessListen Labs is entering a massive but fragmented market. Let me click on that button versus an open ended response. When asked about the tension between speed and rigor — the long-held belief that moving fast means cutting corners — he cited Nat Friedman, the former GitHub CEO and Listen investor, who keeps a list of one-liners on his website.One of them: “Slow is fake.”It’s an aggressive claim for an industry built on methodological caution. And I think like talk to users will be as well, and you’ll have this kind of infinite loop where you can start to ship this truly amazing product, almost kind of autonomously.”Whether that vision materializes depends on factors beyond Listen’s control — the continued improvement of artificial intelligence models, enterprise willingness to trust automated study, and whether speed truly correlates with better products. “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.”The company built what it calls a “quality guard” that cross-references LinkedIn profiles with video responses to verify identity, checks consistency across how participants answer questions, and flags suspicious patterns. And we built this prototype of what Listen is today.”The founding team brings an unusual pedigree. “Can you not just make recommendations, but also create spawn agents to either change things in code or some customer churns? His startup, Listen Labs, needed to hire over 100 engineers, but competing against Mark Zuckerberg’s $100 million offers seemed impossible. “We wanted users to share how Copilot is empowering them to bring their best self forward,” Patel said, “and we were able to collect those user video stories within a day.” Traditionally, that kind of work would have taken six to eight weeks.Simple Modern, an Oklahoma-based drinkware company, used Listen to test a fresh product concept. They can then plug that feedback directly into coding tools like Claude Code and iterate.”The vision extends Y Combinator’s famous dictum — “write code, talk to users” — into an automated cycle. A 2024 MIT study found that 95% of artificial intelligence pilots fail to move into production, a statistic Wahlforss cited as the reason he emphasizes quality over demos.”I’m constantly have to emphasize like, let’s make sure the quality is there and the details are right,” he said.But the company’s growth suggests appetite for the experiment. “There’s school, sports, dinner, and homework,” explained Lauren Neville, Director of Insights and Innovation. The winner flew to Berlin, all expenses paid.That unconventional approach has now attracted $69 million in Series B funding, led by Ribbit Capital with participation from Evantic and existing investors Sequoia Capital, Conviction, and Pear VC. The company is building “the ability to simulate your customers, so you can take all of those interviews we’ve done, and then extrapolate based on that and create synthetic users or simulated user voices.”Beyond simulation, Listen aims to enable automated action based on study findings. Microsoft’s Patel said Listen has “removed the drudgery of study and brought the fun and joy back into my work.” Chubbies is now pushing its founder to give everyone in the company a login. Wahlforss described a customer — an Australian startup — that has adopted what amounts to a continuous feedback loop.”They’re based in Australia, so they’re coding during the day, and then in their night, they’re releasing a Listen study with an American audience. Listen validates whatever they built during the day, and they get feedback on that. Wahlforss described how the artificial intelligence “through conversations, realized there were like issues with the the kids short line, and decided to, like, interview hundreds of kids. “Teams that use Listen bring the customer into every decision, from marketing to product, and when the customer is delighted, everyone is.”Why traditional market study is broken, and what Listen Labs is building to fix itListen’s artificial intelligence researcher finds participants, conducts in-depth interviews, and delivers actionable insights in hours, not weeks. You can kind of double check if they actually know what they’re talking about. Sling Money, a stablecoin payments startup, can create a survey in ten minutes and receive results the same day.”It’s a total game changer,” said Ali Romero, Sling Money’s marketing manager.Wahlforss has a different phrase for what he’s building. Some got hired. “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 study Manager at Microsoft.With Listen, Microsoft can now get insights in days, and in many cases, within hours.The platform has already powered several high-profile initiatives. And the problem is you can’t scale that.”The platform works in four steps: users create a study with artificial intelligence assistance, Listen recruits participants from its global network of 30 million people, an artificial intelligence moderator conducts in-depth interviews with follow-up questions, and results are packaged into executive-ready reports including key themes, highlight reels, and slide decks.What distinguishes Listen’s approach is its use of open-ended video conversations rather than multiple-choice forms. Wahlforss’s co-founder “was the national champion in competitive programming in Germany, and he worked at Tesla Autopilot.” The company claims that 30% of its engineering team are medalists from the International Olympiad in Informatics — the same competition that produced the founders of Cognition, the artificial intelligence coding startup.The Berghain billboard stunt generated approximately 5 million views across social media, according to Wahlforss. “We had all these users, and we were thinking like, okay, what can we do to get to know them better? Wahlforss cited study from Andreessen Horowitz estimating the market study industry at roughly $140 billion annually, populated by legacy players — some with more than a billion dollars in revenue — that he believes are vulnerable to disruption.”There are very much existing budget lines that we are replacing,” Wahlforss said. You want more of it,” Wahlforss explained. It hires engineers for non-engineering roles across marketing, growth, and operations — a bet that in the artificial intelligence era, technical fluency matters everywhere.Synthetic customers and automated decisions: what Listen Labs is building nextWahlforss outlined an ambitious product roadmap that pushes into more speculative territory. People are actually not honest on surveys.” The alternative, one-on-one human interviews, “gives you a lot of depth. “We don’t train on any of the data,” Wahlforss said. So the researchers on the team can do an order of magnitude more study, and also other people who weren’t researchers before can now do that as part of their job.”Inside the elite engineering team that built Listen Labs before they had a working toiletListen Labs traces its origins to a consumer app that Wahlforss and his co-founder built after meeting at Harvard. You can ask follow up questions. Two, they’re kind of stuck in this old paradigm of choosing between a survey or interview, and they also take months to work with.”But the more intriguing dynamic may be that artificial intelligence-powered study doesn’t just replace existing spending — it creates fresh demand. “We will also scrub any sensitive PII automatically so the model can detect that. “I had to find a way to hear from them that fit into their schedules.”The company also discovered product issues through artificial intelligence interviews that might have gone undetected otherwise. It just generates much more honesty.”The dirty secret of the $140 billion market study industry: rampant fraudListen finds and qualifies the right participants in its global network of 30 million people. “But now we fixed that situation.”The company grew from 5 to 40 employees in 2024 and plans to reach 150 this year. Can you give them a discount and try to bring them back?”Wahlforss acknowledged the ethical implications. “We did not have to replace any responses because of fraud or gibberish information,” said Gabrielli Tiburi, Assistant Manager of Customer Insights at Emeritus.How Microsoft, Sweetgreen, and Chubbies are using artificial intelligence interviews to build better productsThe speed advantage has proven central to Listen’s pitch. “We built this consumer app that got 20,000 downloads in one day,” Wahlforss recalled. And there are times when, for example, you work with investors, where if you accidentally mention something that could be material, non public information, the artificial intelligence can actually detect that and remove any information like that.”How artificial intelligence could reshape the future of product developmentPerhaps the most provocative implication of Listen’s model is how it could reshape product development itself.
(This article was automatically generated from an AI news feed and rewritten for originality.)
