- 0:00 Salesforce agreed to acquire Listen Labs
- 0:28 What Salesforce said, and what it didn't
- 1:02 Where Listen Labs is strong
- 1:22 An independent alternative you run yourself
- 1:51 How depth works
- 2:27 Quality, cost, and the next study
- 3:06 The other alternatives, by job
- 3:40 Run the comparison on your own work
Video transcript
On September twenty-ninth, Salesforce signed an agreement to acquire Listen Labs. The deal has not closed. Salesforce expects it to close in the final quarter of its fiscal year, which ends in January 2027, and it still needs regulatory clearance. The product did not change the day the news broke, but the buying decision did, because ownership and direction are now part of it. So if your team runs research on Listen Labs, or was about to, this is a sensible time to look at the alternatives. The right one depends on the job, and each tool here is matched to the job it does best. Here is what Salesforce has said. It describes Listen Labs' customer research and its human simulation as complements to Marketing Cloud, Service Cloud, and its wider AI portfolio. Here is what it has not said. The announcement does not say whether Listen Labs stays available as a standalone product, what happens to pricing and contract terms, or whether you will need a Salesforce relationship to keep using it. None of that is a reason to assume the worst, and all of it is a reason to ask. If you are renewing or evaluating Listen Labs in the coming months, get four answers in writing. Will it stay standalone? How do your contract and pricing carry over? Where will your research data live? And does a Salesforce relationship become a requirement? Start with where Listen Labs is strong, because it is a good product. In User Intuition's own side-by-side testing in June, it stood out for hands-on support and for recruiting hard-to-reach business audiences, the kind of niche recruit where a research team wants a partner, not just software. If your studies depend on that level of service, staying is a reasonable choice, and nothing in the announcement changes that on day one. That said, most studies are not niche recruits. They involve consumers or shoppers, and for that work a hands-on service layer is often more than the brief needs. User Intuition is an independent, research-first platform built for that work. Your team keeps its brief and discussion guide and sets up a study in about five minutes, with no sales call required. You can bring your own participants or recruit from a panel of more than four million people, and run the study as voice, chat, or video interviews. For most audiences, a focused study can go from sign-up to findings in under a day. Depth is where the difference shows. Ask someone why they bought an electric car, and they say they were tired of paying for gas. A survey writes that down and moves on. User Intuition asks why that matters right now, and they say they are trying to be more careful with money. It asks why that matters, and they say it gives their family some stability. Then it goes one level further and asks why stability comes first, and the answer is that they want to be the kind of parent their kids can count on, whatever happens to the economy. That took four questions, and it moved from the price of gas to someone's sense of who they are as a parent. Nobody wrote those follow-ups in advance. The moderator asks each one based on what the person has just said, and that is the part a survey cannot reach. Once the interviews are in, three things matter to a team that pays for research one project at a time. The first is quality. Every interview is checked against the brief for length, depth, and coverage before billing, and an interview that fails is not charged, so there is no refund to chase. The second is cost. It is thirty dollars per quality interview with no subscription, so five interviews with your own participants come to a hundred and fifty dollars, or three hundred dollars with standard panel recruitment. The third is what happens next. User Intuition reviews the evidence against each learning goal and recommends the follow-up study, rather than stopping at a report. In a forty-three person study of Walmart shoppers, most said they would return, and it flagged that the deciding question, whether price, proximity, or familiarity drives the next store choice, still needed testing. If depth interviews are not the job, the shortlist changes. Conveo suits large brands that want AI-led voice and video interviews combined with structured methods such as MaxDiff. Strella is a highly configurable AI interview platform, for teams that want to control how each study runs. Outset stands out for flexible reporting, with highlight reels that carry customer moments to stakeholders. Great Question lets team members and stakeholders join live research sessions without interrupting them. Discuss makes sense if you want a single place for human-led interviews and self-paced feedback. And Dscout is the choice for diary studies, when an experience unfolds over days or weeks. The quickest way to decide is to test it on your own work. Take the next question you would have sent to Listen Labs, and run it as a five-interview study in User Intuition. Your first three interviews carry no platform fee. Then read the interviews and findings next to what you have today, and let the evidence make the call, including when the answer is still Listen Labs. Start at www.userintuition.ai.
How we picked these eight: each alternative is matched to the one job it does best, judged from the vendor’s own product pages and documentation in September and October 2026. We did not score moderation quality: Listen Labs relaunched its AI Interviewer on September 1, 2026, and observations from before that date no longer describe the current product. Start from the job in your next brief, then read the section for the tool that fits it. Salesforce’s definitive agreement to acquire Listen Labs, signed September 29, 2026 and not yet closed, adds one more check to every shortlist: whether the vendor’s ownership and roadmap suit your clients and your renewal date.
What should you look for in a Listen Labs alternative?
Listen Labs sets a high bar on breadth, so check which of its capabilities your studies use before you switch. It advertises interviews in 120+ languages and variants (its FAQ cites 40+ with voice moderation), against 80+ on User Intuition. Its interviewer can watch a shared desktop screen (June 2026) and ask about files participants upload (July 2026). It runs ranking, MaxDiff with TURF and Gabor-Granger pricing tests inside a study, and Pulse tracks a metric such as brand health across waves. It also states SOC 2 Type II, ISO 27001, ISO 27701 and ISO 42001 compliance today. If your work depends on a language outside User Intuition’s list, on in-study quant modules, or on a completed SOC 2 report, weigh Listen Labs first; Conveo is the other option for structured quant inside an interview program. If it depends on deep one-to-one interviews you design yourself, priced per project, User Intuition is the closer fit.
Which Listen Labs alternative fits your research needs?
Choose User Intuition for self-serve depth interviews and evidence review with published project costs. Choose a broader method suite when the brief depends on live group discussion, observed product tasks, or diary activities. The table identifies the most useful reason to shortlist each option.
| Platform | Strongest reason to shortlist it | What that enables |
|---|---|---|
| User Intuition | Adaptive depth interviews, evidence review, and pay-as-you-go pricing | Run a client or internal study directly, then prioritize consequential follow-ups |
| Conveo | AI-led voice and video interviews with structured methods | Run always-on enterprise programs that combine interview depth with MaxDiff and concept testing |
| Strella | Voice-to-voice AI interviews with human-led and hybrid options | Mix AI-moderated and researcher-moderated sessions in one program |
| Outset | Flexible reporting with highlight reels | Carry findings to stakeholders through reels and presentation outputs |
| Great Question | Stakeholders join live research sessions | Let product, design, and marketing teams watch interviews without interrupting |
| Discuss.io | One place for human-led interviews and self-paced feedback | Combine live sessions and asynchronous feedback in one program |
| Dscout | Diary studies | Understand habits and experiences as they unfold over days or weeks |
| Usercall | Research at real product moments | Talk to customers closer to the behavior you want to understand, then turn those conversations into evidence-backed findings |
1. User Intuition: interview depth and evidence review, paid per project
User Intuition is an AI-moderated interview platform that gives research teams and agencies the depth of a senior researcher at the scale of a survey, with vetted respondents, their own methodology and evidence they can trace to the verbatim. It is independent. Researchers keep the brief and discussion guide, choose their participants, and inspect findings alongside the original interviews. Agencies can retain their methodology and client relationship while expanding fieldwork capacity across projects.
How does User Intuition differ from Listen Labs?
Three differences are specific to Listen Labs and easy to check. First, the price is on the website. User Intuition charges $30 per quality voice interview with no subscription; Listen Labs has no pricing page and describes a subscription with credits spent per participant, sold through a demo and pilot to organizations over 100 employees. Second, depth is the default. User Intuition’s 20–30 minute interviews ladder 5–7 levels unless you set otherwise; in Listen Labs the researcher picks a follow-up setting for each question, from none up to 2–3 follow-ups, as its docs still described on September 26, 2026, after the September 1 relaunch of its AI Interviewer. Third, ownership. User Intuition is independent; Salesforce signed a definitive agreement to acquire Listen Labs on September 29, 2026, and the deal has not yet closed.
Both platforms bill only for interviews that pass a quality bar, both search across past studies (Listen Labs through Research Library, User Intuition through its Customer Intelligence Hub), and both offer an API and MCP connector, so none of those decide the choice.
Why do research teams and agencies choose User Intuition?
Among these eight, User Intuition is the pick when the job is depth interviews your own team designs. Depth comes first, then a guide that runs exactly as written, then respondents and findings a client can audit, then reach across modes and markets, then cost. Your method holds through fieldwork: required questions stay pinned in your order and wording, monadic and sequential monadic cells run in parallel and land side by side for comparison, and screeners with hard quotas keep each cell to plan. Sample comes from a customer list, Prolific, Cint / Lucid, CloudResearch or any provider through a custom link, and each client’s work sits in its own isolated workspace. On the respondent side, a person listens to every panelist’s interviews before accepting them onto the panel, every session is screened for AI-generated or coached answers, and the price of the next project is known before the proposal goes out. The full comparison lists every capability behind those reasons.
How does User Intuition uncover motivations beyond the first answer?
User Intuition uses adaptive laddering to move from what a participant says to the experience, consequence, and motivation behind it. The approach is informed by Reynolds and Gutman’s laddering research, which connects product attributes with consequences and personal values. That helps a researcher distinguish a requested feature from the benefit it needs to deliver, and turn the finding into a product priority or positioning decision.
For example, an answer about convenience can lead to the circumstances that make a task difficult, the effect on the person’s day, what that costs them, why that cost matters now, and what it says about the kind of person they want to be: five or six rungs from a feature to a value. The electric-car example in the video above shows only the first four rungs; a full interview keeps going, 5–7 levels by default. User Intuition follows those explanations toward the learning goals without requiring the researcher to prewrite every follow-up branch.
How does User Intuition reduce the risk of weak findings?
User Intuition checks each interview against the brief for Length, Depth, and Coverage before billing. Failed interviews are not charged. Your team avoids paying for unusable sessions or spending time requesting refunds.
User Intuition also reviews evidence against each learning goal: what the interviews support, which experiences or explanations are missing, and which gaps matter most to the decision. It recommends deeper analysis when existing interviews contain the needed evidence, or focused follow-up research when they do not. That review draws on Malterud et al.’s information power and Hennink et al.’s meaning-saturation research, which separate a theme the interviews mention from one they explain.
In our 43-participant Walmart study, thirty-six shoppers said they would shop there again. That answer did not settle the decision that matters to a retailer: whether price, proximity or familiarity drives the next store choice. The evidence review flagged that gap and recommended a follow-up that recontacts shoppers after a comparable trip and compares those who returned with those who went elsewhere.
When you are choosing between alternatives, run the same five-interview brief on your top two and compare the finished interviews, not the demos. User Intuition’s sample study shows what its side of that comparison looks like.
How quickly can a team start and scale a study?
User Intuition provides five-minute self-serve setup without a mandatory sales call. Interviews run concurrently without a platform-imposed hourly cap. Panel studies return 200+ interviews in 24 hours; with your own participants, interviews run in parallel as they respond. Findings arrive as quality interviews finish.
Interviews run as voice, video, or chat in 80+ languages. The direct Listen Labs comparison covers moderation, quality billing, security, and commercial terms row by row, including the rows where Listen Labs leads.
Can an AI agent help run the research?
Yes. User Intuition’s first-class API and MCP access lets an agent search past studies, prepare the exploratory study, obtain a recruiting estimate, launch within approved spend, and retrieve source-linked findings. The evidence assessment can then guide a proposal for the next study. Listen Labs also offers a public API and an MCP connector, so the deciding question is which steps your team wants an agent to run.
2. Conveo: structured methods such as MaxDiff with AI interviews
Conveo fits enterprise insights teams that want AI-led voice and video interviews combined with structured research methods. Conveo’s platform runs structured methods inside the AI interview: MaxDiff (since April 2026) and Van Westendorp and Gabor-Granger pricing questions (since June 2026), with conjoint, Kano and TURF listed as coming soon. Guides rotate concepts in monadic or sequential-monadic cells, and video interviews add facial coding and emotion detection. Its StoryLines product runs always-on programs, such as monthly brand trackers, that feed a shared knowledge base.
Conveo fits best when a large brand runs recurring studies across markets, where the team wants quantitative method alongside interview depth and a program that continues over time. Conveo sells through a demo rather than published pricing. Compared with Listen Labs: neither publishes prices for its interview platform, and both run structured methods inside the interview. Conveo has no first-party panel and recruits through partner panels such as Respondent or your own list, while Listen Labs recruits from a network it puts at 30M–50M+ respondents, drawn from partner panels plus its own database. User Intuition’s contrasting fit is a published per-interview price and a study your team can launch directly, one project at a time.
3. Strella: voice-to-voice interviews with human-led and hybrid options
Strella fits teams that want real-time voice-to-voice AI interviews and the option to run human-led (beta) or hybrid studies alongside them. Strella’s platform also combines participant sourcing, adaptive interviews, researcher-moderated sessions, research chat, and video highlight reels.
Strella earns the shortlist when a program mixes AI-moderated sessions with researcher-moderated ones, or when the team wants Strella’s Advisory team to run part of the work. Strella also offers Claude and ChatGPT connectors for launching studies and working with research evidence. Compared with Listen Labs: neither publishes prices, and in both the researcher configures follow-up depth. Strella’s distinguishing features are real-time voice-to-voice moderation and human-led or hybrid sessions; Listen Labs’ are in-house senior researchers, managed recruiting for niche audiences and quant modules such as MaxDiff inside the study. User Intuition’s contrasting commercial fit is a directly accessible, published per-interview price for teams funding work one project at a time.
4. Outset: flexible reporting with highlight reels
Outset fits research teams that want flexible reporting, with synthesis, highlight reels, and presentation outputs built into the workflow. Its context-aware moderator runs AI interviews across text, voice, and video and responds to audio and visual cues. Outset’s subscription plans use custom pricing, with feature access and services varying by plan and add-ons.
Reporting matters most when findings must reach stakeholders who will not read a full report. Highlight reels and presentation-ready outputs shorten that step, and optional research services help with complex fieldwork. Compared with Listen Labs: neither publishes prices, and both recruit mainly through partner panels, with Outset citing 25+ panel integrations. Outset lets the researcher allow up to 10 follow-ups on a question in its Abyss mode, against Listen Labs’ setting of none to 2–3. Our Outset alternatives guide compares the two head to head. User Intuition offers a simpler entry point when a team wants to design and run its next depth-interview study directly, with the price visible before committing.
5. Great Question: stakeholders join live research sessions
Great Question fits teams that want colleagues and stakeholders to watch research as it happens. Its Observer Rooms let product managers, designers, and other stakeholders join a live interview without interrupting it; participants do not see observers, and observer seats are free. Great Question’s platform also combines participant recruitment, a research CRM, and an AI-powered repository.
Great Question suits a product organization that wants more people to hear customers directly without asking each of them to run research. Great Question offers a free study and publishes its pricing. Compared with Listen Labs: Great Question publishes seat pricing where Listen Labs publishes none, and it is built around research operations, with AI moderation sold as an Enterprise add-on; Listen Labs is built around AI-moderated interviews with in-house researchers alongside. User Intuition’s contrasting fit is depth-interview fieldwork with quality checks before billing and evidence review, paid per quality interview with no subscription.
6. Discuss.io: one place for human-led interviews and self-paced feedback
Discuss.io fits teams that want a single place for human-led interviews and self-paced feedback. Discuss.io’s platform supports live interviews and focus groups, AI-led conversations, and self-paced feedback, alongside uploaded research and a workspace for querying existing findings. Agencies can choose the approach appropriate to a particular client engagement while keeping the research in one environment.
Human-led sessions are particularly relevant when group interaction or a moderator’s live intervention is part of the research design. Self-paced feedback and AI interviews cover other briefs within the same program. That combination suits an agency delivering a mix of live client sessions and automated fieldwork across engagements. Compared with Listen Labs: both sell quoted plans with optional services, but Discuss.io adds live human-moderated interviews and focus groups with observers, while Listen Labs centers on AI-moderated interviews with in-study quant modules and in-house senior researchers.
7. Dscout: diary studies across days and weeks
Dscout fits research built on diary studies, where participants record an experience over days or weeks, such as a week of meal planning, product use at home, or a changing customer journey. Dscout’s platform also includes field studies, usability testing, surveys, and interviews. Its AI Studio supports study drafting, adaptive moderation, and analysis with sources.
The reason to choose Dscout is the ability to build multiple participant activities into a study and capture context close to the experience. That is different from asking someone to reconstruct everything in one conversation. A diary study can show how a habit changes, which interruptions recur, and how people adapt, making Dscout particularly relevant to journey research and longitudinal product studies. Compared with Listen Labs: both sell customized subscriptions without published prices, but Dscout builds several participant activities into one study over days or weeks, while Listen Labs’ Pulse runs conversational tracking waves on metrics such as brand health or NPS.
8. Usercall: research at real product moments
Usercall fits product and research teams that want customer conversations to happen close to the moments they are trying to understand. Rather than relying only on standalone studies and on participants recalling an experience later, teams can use Usercall’s research triggers to reach relevant customers in context, run adaptive voice interviews, and turn those conversations into qualitative findings linked back to the participant evidence. Its platform also offers a Figma plugin, recruitment from a global consumer and B2B panel, and MCP access for creating studies and retrieving results.
Usercall suits product, UX, and research teams running ongoing discovery, where the question is why customers behave the way they do while the experience is still fresh. Usercall sells credit subscriptions starting at $89 a month. User Intuition’s contrasting fit is a planned depth-interview study on your own guide, paid per quality interview with no subscription.
What does a five-interview User Intuition study cost?
Five quality voice interviews cost $150 in User Intuition platform fees with your own participants, or $300 with standard panel recruitment. No monthly subscription is required. The published User Intuition pricing lets a research team or agency budget the next project before fieldwork.
| Cost component | Your own participants | Standard panel recruitment |
|---|---|---|
| Platform fee for five quality voice interviews | $150 | $150 |
| Recruitment | Your existing sample | $30 per participant |
| Five-interview total | $150 platform fee | $300 including standard recruitment |
| Required subscription | None | None |
Incentives you arrange for your own participants are separate. Specialist audiences require a recruiting quote. Five interviews set the starting price; User Intuition’s evidence review helps determine which questions need further investigation.
Listen Labs publishes no prices; it describes a subscription with credits that vary by audience. Our Listen Labs pricing guide covers the current model and a dated buyer-reported quote. Compare the same audience, modality, service scope, and usable interview count when assessing total cost.
How should the Salesforce announcement affect your choice?
The announcement makes ownership and future platform direction relevant to the shortlist. Salesforce describes customer research and human simulation as complements to Marketing Cloud, Service Cloud, and its broader AI portfolio. Our Salesforce–Listen Labs explainer separates the announced transaction from the practical questions buyers face.
User Intuition’s independent position is useful because the buying path is concrete: your team can commission a study directly, set its method and budget, and choose the next research step from the evidence. That fits agencies serving multiple clients and research teams that purchase studies project by project.
Start with the next decision your team needs to make. See how agencies use User Intuition, or follow the guide to running your next study after Listen Labs.