Listen LabsTranslation site

Company Overview

Listen Labs is a business-to-business customer research company founded in San Francisco in 2023 by Alfred Wahlforss and Florian Juengermann. It leverages artificial intelligence in interviews and research processes to help product managers, brand teams, and user researchers understand why customers choose, abandon, or misunderstand a product. The company was named to Forbes’ 2026 AI 50 list.

The platform focuses on feedback provided by real respondents, enabling companies to explore new concepts and advertising ideas while continuously monitoring brand awareness. Businesses can import their customer lists and research outlines into the system, transforming scattered interview data into a searchable knowledge base.

Milestones

The company’s early efforts stemmed from an app the team developed for themselves in 2023 to better understand users: they created an AI-powered interview tool capable of asking questions. In April 2025, Listen was officially launched, and subsequently expanded from a single interview session to a complete process encompassing recruitment, analysis, and customer insight.

On September 29, 2026, Salesforce announced that it had signed a definitive agreement to acquire Listen Labs, with the aim of enhancing the customer insights capabilities of its marketing, services, and AI businesses. The signing of the agreement does not constitute completion of the transaction; this article describes the transaction’s status as of the date of the announcement. Future details regarding the company’s integration with Salesforce products, service arrangements, and the actual progress of the transaction should still be subject to subsequent official announcements from both parties.

Products & Services

• Study Design:It generates questions and follow-up prompts based on research objectives, and also allows researchers to upload their own interview outlines, enabling them to maintain control over the direction of the investigation.
• Recruiting Respondents and AI Interviews:Helps identify eligible participants and supports companies’ own contact lists; the AI moderator follows up with additional questions based on responses, making it suitable for multilingual and cross-market research.
• Concept and Usability Testing:Collect explanatory feedback on prototypes, advertising messages, product experiences, and brand perception; this can be combined with observing users' usage processes via screen sharing.
• Insights and Reuse of Data:Organize the themes and key points from interviews, and search historical materials by audience or topic to ensure that new research builds on existing knowledge.

core technology

Listen’s technical focus is on integrating conversational AI into the research process, rather than simply transcribing audio recordings. Dynamic follow-up questions adapt to the respondent’s previous answer, and the analysis system then identifies common themes across multiple responses. Researchers still need to define objectives, recruitment criteria, and interpretive boundaries to avoid mistaking fluent summaries for representative conclusions.

The platform consolidates interview transcripts, audience data, and analytics results into a single workspace, facilitating cross-project comparisons. Its official website also highlights features for ongoing brand tracking and customer behavior simulation; these simulations serve as supplementary decision-making tools based on existing data, but actual requirements should still be validated through real user feedback.

Compiling interviews into a report is only one part of the research process. For example, when a company tests a new product, it also needs to compare the responses of buyers and non-buyers, be mindful of biases caused by recruitment channels, and refer back to the original statements to ensure that the summary does not omit any conditions. While platforms can reduce the cost of data organization, whether the research design is sound determines whether the results can answer genuine business questions. Teams can cross-reference ongoing interviews with existing behavioral data to identify discrepancies between attitudes and actual choices, and then determine what additional evidence is needed.

development prospect

From a product evolution perspective, Listen has the potential to transform what was once infrequent and fragmented qualitative research into a continuous source of business insights. If integration with the Salesforce ecosystem proceeds as planned, customer feedback may be more easily incorporated into marketing, service, and product decision-making processes; however, the extent of this synergy will depend on the progress of the deal and the effectiveness of the implementation.

Long-term value depends on the quality of the sample, whether follow-up questions minimize leading, whether the analysis preserves a small number of important opinions, and how the company manages privacy and research ethics. For users, the prudent approach is to view it as a tool for expanding research coverage and to have key conclusions and action recommendations reviewed by professionals.