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Listen Labs

Listen Labs designs research studies, recruits participants and runs AI-moderated video, audio or text interviews, then turns the answers into reports, clips and slides for insights, UX and brand teams.

AnalyticsResearch#Transcription#market research#research platform
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Sep 28, 2026
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Listen Labs Product Information

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What is Listen Labs?

Listen Labs is an AI market research platform that plans a study, finds participants, lets an AI moderator run the interviews and then turns the conversations into analysis and deliverables. The company frames the product as a way to learn what people think, why they think it and what to do about it, based on real human interviews. Interviews can run over video, audio or text.

Listen Labs is the trade name of Merlin AI, Inc., a Delaware corporation, and customers sign Order Forms with that company. It is sold as an enterprise service, with commercial terms set in the Order Form and the Master Service Agreement (MSA).

Company background

Listen Labs announced a Series B that it describes as bringing total funding to $100M, led by Ribbit Capital with Evantic, Sequoia Capital, Conviction and Pear VC participating. Independent technology reporting at the time put that round's valuation at $500 million and total capital at $100 million.

In September 2026, independent reporting that cited several people with knowledge of the matter said Listen Labs had signed a term sheet for a $125 million Series C at a $1.5 billion valuation, and that the round never closed. The same report said Salesforce had recently held talks to buy Listen Labs for around $2 billion, adding that the talks were not finalized and might not result in a deal. These are ownership signals, not evidence of research quality.

Core features

Study design and AI moderation

  • Study drafting: Listen drafts objectives, questions and probing context from a stated research goal, or it works from an interview guide that the team uploads.
  • Adaptive probing: In AI-moderated interviews, the moderator asks for the reasoning behind answers, digs into interesting points and follows conditional instructions, such as asking which competitor a respondent mentioned and why.
  • Topic boundaries: The moderator is described as operating only inside the research objectives and topic boundaries that the team approves.
  • Workspace rules: Organization-wide rules can block sensitive topics, prohibited claims and brand-risk language across every study.

Probing depth is set per question, while workspace rules apply to every study in the organization.

Quality Guard

  • Fraud signals: Quality Guard flags copy-pasted answers, screener contradictions and speeding as interviews run, plus tab-switching, AI-generated voices and avatars, and substandard videos.
  • Grading: Each response is graded live on a five-point scale (Excellent, Good, Average, Low and To Review), and close calls go to Listen Labs' own research team before a final decision.

Analysis, reporting and Research Agent

  • Traceable deliverables: Listen builds deliverables from highlight reels to slides, and the company says every claim traces back to a real interview.
  • Research Agent analysis: Research Agent segments respondents, compares groups and runs significance testing from plain-language requests.
  • Export formats: Research Agent can format findings into slides using a company template, produce a downloadable memo or export a theme-coded CSV.

Specialized study modules

  • Gabor-Granger price tests: Each buyer moves up or down a price ladder based on earlier answers until the test finds the maximum price that person would pay.
  • MaxDiff: MaxDiff studies include Portfolio Optimization, which looks for the mix of options that reaches the widest audience.
  • Pulse tracking: Pulse keeps study design, audience and screening constant from wave to wave so that trend lines stay comparable.
  • Visual Insights: In screen-share studies, a video model writes a timestamped log every second and records each significant on-screen change.
  • Emotional Intelligence: This module reads micro expressions, tone of voice and word choice together, and its description cites 50+ languages.

Listen Twins

Listen Twins is a separate product that returns simulated answers instead of fielding a new study. Each twin is built from one-to-one interviews with the customer's audience and, in the company's words, is purpose-trained on the outcomes the customer cares about. When a twin lacks enough signal, it is designed to answer "I don't know" rather than guess.

Guide

  1. Create the study. Click New Study and add objectives. An existing discussion guide can be uploaded directly, and the AI parses it into the study.
  2. Set workspace defaults once. Admins can define workspace guidelines that apply automatically to every new study created in the workspace; existing studies are not updated retroactively.
  3. Choose recruitment. A single study can run several recruit groups, for example one from Listen's panel and one from the team's own customer list.
  4. Publish, then launch. Publishing a study does not send it to participants; recruitment starts from the Recruit tab.
  5. Soft launch first. Set a low response limit, such as N=10 against a target of N=100, so recruitment pauses automatically and the guide can be adjusted.
  6. Fund incentives. Respondent incentives are paid from a balance that must be loaded into the Listen Labs account before payout.

Listen Labs use cases and examples

These examples come from Listen Labs' own pages; case-study results are not independently verified.

  • Usability testing: Participants share their screen while they walk through a product.
  • B2B and expert audiences: Listen lists recruiting and interviewing niche, low-incidence and professional audiences among its core use cases.
  • Scaling a moderated finding: Listen suggests checking a theme heard in 5 human-moderated sessions with an AI study of the next 50 respondents.
  • Multi-location consumer research: In the vendor-published Sweetgreen case study, the restaurant chain scaled research across 300+ US locations.
  • Enterprise product research: A Microsoft research manager quoted in another vendor case study says she can reach hundreds of users at one third of the cost.

Who is it for

Likely fit

  • Consumer insights, brand, product and UX research teams that field studies regularly.
  • Teams with mixed permissions: admins manage members, researchers see and launch studies, and collaborators get read-only access to results.
  • Teams seeking hard-to-reach participants: niche healthcare audiences, groups under 1% incidence or enterprise C-suite go through managed recruitment support.

Weaker fit

  • Buyers who need a published price or a monthly plan before speaking with sales.
  • Teams that mainly want to analyze interviews already recorded elsewhere, because uploading full unstructured interview transcripts is not currently supported.
  • Projects that need to publish identifiable participant video, which the contract restricts.

Platforms

Teams build studies and read results in the Listen Labs web application.

  • Participant iOS app: The Listen Labs iOS app displays studies so participants can view tasks, answer questions and submit responses from their phone.
  • Mobile screen recording: Mobile screen recording is currently offered only on iOS devices.
  • API: An API supports study creation, launch and response retrieval, and each API key is scoped to a single organization.
  • MCP server: A Listen Labs MCP server connects Claude, ChatGPT, Codex and other MCP clients to a Listen Labs account.
  • MCP permissions: The integration only sees and changes studies that the connected Listen Labs user can already access.
  • Rally: With the Rally integration, a participant's status in Rally updates automatically to In Progress and then to Complete.

Language and panel coverage figures

Coverage numbers differ from page to page and are quoted here as stated.

  • The homepage says interviews run globally, 24/7, across 120+ languages.
  • The Quality Guard page says the same scoring applies across 110+ languages and 70+ countries.
  • The documentation FAQ states support for 90+ languages and 40+ languages with voice moderation.
  • The voice interviewer guide lists multiple voice options for each of 42 supported languages.
  • The multi-market use-case page says Listen translates and transcribes between more than 50 languages.
  • The recruiting guide describes a network of 30M+ verified respondents across 45+ countries and 100+ languages.
  • The homepage describes a global network of 50M+ participants.

Pricing

No price list or per-interview rate was found on the pages checked in this round; Listen Labs pricing is set per customer in the Order Form. Feature pages show a Try for Free button that leads to account sign-up, without stating what free access includes.

Contract billing terms

The MSA (last updated Feb 6, 2026) sets these terms:

  • Currency: Fees are set in the Order Form or Statement of Work in U.S. dollars.
  • Credits: Customers may buy Credits for certain Services under the Order Form.
  • Payment timing: Unless the Order Form says otherwise, invoices are due within thirty days of the invoice date.
  • Auto-renewal: Services renew for a term equal to the expiring Order Form Term unless either party gives non-renewal notice at least thirty days before it ends.
  • No proration or refunds: Except for Listen Labs' uncured material breach or other stated exceptions, fees are not prorated on cancellation and paid fees are non-refundable.
  • Unused services: No refund applies if the customer chooses not to use Professional Services during the Order Form Term.
  • Late payment: Unpaid invoices can carry a finance charge of 1.5% per month or the maximum permitted by law, whichever is lower.
  • Suspension: After ten days' written notice, Listen Labs may suspend or terminate the Services for payments more than thirty days past due.

Costs inside a study

  • Quality replacements: When Quality Guard flags a low-quality participant, Listen recruits a replacement at no extra cost; customers pay only for completes that meet its bar.
  • Wallets: API wallets report separate recruitment and project credit balances for each organization.
  • Professional audiences: The Professionals panel carries a higher cost per complete than general-population recruiting.

Listen Labs alternatives

Independent technology reporting names Simile, Outset, Keplar and Aaru as competitors in AI customer research. The same reporting separates platforms that automate interviews with real people from startups such as Aaru and Simile that simulate human behavior and predict responses without interviewing anyone. Listen Labs' core product belongs to the first group, while Listen Twins adds a simulation option.

Listen Labs' own comparison pages are vendor claims, not neutral tests:

  • Qualtrics: Listen's comparison page says most platforms, like Qualtrics, use AI only for post-study summaries.
  • Outset: Listen's comparison page says customers choose it over Outset for a smoother user experience, more robust panel recruitment and better white-glove service.
  • Combining instead of switching: With the Qualtrics integration, one set of participants can answer a Qualtrics survey and then a Listen interview.

Limitations

Product and workflow limits

  • Output needs human review: Under the MSA, the customer must independently verify all Output through human review and expert consultation before relying on it.
  • Screen-share scope conflict: The documentation FAQ says single-tab sharing isn't available.
  • Screen-share guide wording: The screen-sharing guide says participants can share their full screen, an application window or a single browser tab.
  • Charts in slides: Percentage charts aren't available in automatic PowerPoint generation.
  • Quota timing: Quotas are checked only after the complete screener is finished.
  • Editing live studies: Deleting questions that already have responses removes those answers from analysis.
  • Niche fielding speed: Very niche professional targets field more slowly.

Contract limits on participant data

  • Internal use only: Participant Data may not be used for public distribution, marketing or resale without Listen Labs' written authorization.
  • No identifying disclosures: Customers may not publicly disclose Participant Data that identifies participants by name, voice or image without Listen Labs' prior written consent, except as law requires.
  • No sensitive data collection: Customers may not intentionally collect or request sensitive Personal Data from participants through the Services.
  • No MNPI: Customers may not use the Services to intentionally solicit, collect or process material non-public information.

Data use, privacy and compliance statements

Statements about AI training differ in wording:

  • The MSA says Listen Labs will not use Customer Data for any other purpose, including training any AI models.
  • The Quality Guard page says customer data is never used to train AI models.
  • The AI code of conduct says Listen Labs does not use any data it collects to train its AI models.
  • The Twins page says twins keep improving with new studies, context and company data, without explaining how this relates to the statements above.

The AI code of conduct commits to not sharing any collected data with third parties. The Study Privacy Policy, last updated Feb 24, 2026, says study responses are shared with the Research Organization that commissioned the study. It also lists service providers such as cloud storage, which may not use the data for their own purposes. The same policy allows aggregated, de-identified or anonymized participant data to be used to improve the platform.

Storage and certification claims vary by page:

  • The Study Privacy Policy says participant Personal Data is stored on U.S.-based servers.
  • The Quality Guard page claims SOC 2 Type II, GDPR and CCPA compliance, triple ISO certification and optional EU data hosting.
  • The MSA states SOC 2 Type 2 compliance and says the report is provided on request under confidentiality terms.
  • The comparison page lists SOC 2, ISO 42001/27001/27701 and HIPAA compliance; HIPAA does not appear in the policies reviewed.
  • Participant data is kept for the period the Research Organization defines or as required by law.

The Study Privacy Policy says Listen Labs does not knowingly collect data from children under 13 and seeks parental consent for ages 13 to 15 where required. The App Privacy Policy says the mobile app is not intended for anyone under 16. The Consumer Health Data Privacy Policy says studies are not designed to seek health information and the platform is not meant for medical records. Participants are asked for consent before a study to process any health information they choose to share.

On ownership, the MSA says the customer retains all rights, including intellectual property rights, in Customer Data. If any Output is not automatically the customer's intellectual property, the MSA says Listen Labs assigns it to the customer.

FAQ

Q1. How much does Listen Labs cost?

No public price was found. Fees are set in each customer's Order Form, renew automatically and are generally non-refundable.

Q2. Does Listen Labs use my data to train AI models?

Three official pages say no, though the Twins page describes twins improving with company data.

Q3. How many languages does Listen Labs support?

Figures range from 42 voice languages in the documentation to 120+ on the homepage.

Q4. Are Listen Labs interviews with real people?

Yes for the core product; Listen Twins is a separate simulation product built from earlier interviews.

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