Decode vs ListenLabs

Both platforms run AI-moderated qualitative interviews. The difference lies in what they measure and how far beyond the interview each one goes. 

Decode vs ListenLabs at a glance 

ListenLabs is optimized for fast, large-volume AI-moderated interviews with a large verified panel and strong speed-to-insight. Decode captures measured emotion, attention, and voice as dedicated research technology across a unified platform that spans interviews, creative testing, usability, and consumer research. 

The core distinction: ListenLabs applies Ekman-based emotional intelligence from the interview conversation. Decode measures facial emotion, eye gaze, and voice as core research technology — in the same session, across methods beyond interviews alone. 

What is ListenLabs?  

ListenLabs is an end-to-end AI-moderated research platform built for enterprise consumer insights and brand teams. Its model covers study design, recruitment through a verified panel of 30M+ participants across 45+ countries, AI-moderated interviews (video, voice, and text), fraud detection, and a cross-study knowledge base called Mission Control. 

Core strengths: sub-24-hour turnaround for fielded studies, large-scale verified panel reach, adaptive probing, Ekman-based emotional intelligence applied to voice and expression cues from the interview, and strong venture backing. ListenLabs raised significant institutional funding and has built quickly on a foundation of speed and panel scale.  

Typical buyer: enterprise consumer insights and brand teams that prioritize interview speed and recruitment reach for large-scale qualitative programs. 

What is Decode by Entropik? 

Decode is a unified human insights platform built on Emotion AI and Behavioral AI technology. It combines consumer insights research, user research, AI creative testing, AI-moderated interviews, and a searchable research repository in one platform. 

Core technology: 

• Facial Emotion AI

• Eye Gaze Tracking

• Voice Emotion AI

• Attention Measurement

• AI Moderator

Platform modules include Consumer Insights, AI Creative Insights, User Research, Insights Hub, and AI Moderator. 

Verified platform figures: 90%+ facial coding accuracy, 96% eye tracking accuracy, 62 facial expressions tracked, 70+ languages supported, 17 patents, 150+ global brands. 

Typical buyer: consumer insights, CPG, and research teams that need behavioral depth and the ability to run multiple research methods — interviews, creative tests, usability studies — in one platform. 

Decode vs ListenLabs: feature-by-feature 

AI moderation and interview depth 

Both platforms run adaptive AI-moderated interviews. ListenLabs' approach is built around speed and scale — rapid deployment, large panel, and automated probing from a verified recruitment pool. Decode's AI Moderator (Mira) runs text, voice, or video sessions across 70+ languages with real-time adaptive follow-up. 

A relevant industry caveat worth noting for both platforms: Nielsen Norman Group's evaluation of AI interview tools found that current AI moderators have real-world limits in real-time adaptivity — they perform better on structured, well-defined research questions than on deeply exploratory conversations where a skilled human moderator would improvise. This applies across AI-moderation tools, including both platforms reviewed here. 

Emotion and behavioral signal depth 

This is where the platforms differ meaningfully — and where it is important to be accurate rather than overstate. 

ListenLabs applies Ekman-based emotional intelligence: analyzing voice patterns, tone, and expression cues from the interview conversation to surface emotional signals. This is a substantive capability and a genuine strength for interviews where the verbal and para-verbal signal is what matters. 

Decode measures facial emotion, eye gaze, and voice as dedicated research technology applied at the moment of stimulus exposure — not extracted from a conversation afterward. Facial coding at 90%+ accuracy tracks 62 discrete expressions. Eye gaze tracking at 96% accuracy captures exactly where attention lands on a concept, packaging design, or creative stimulus. Voice Emotion AI runs simultaneously. 

The distinction is signal type and measurement method, not presence versus absence of emotion analysis. For research where the stimulus is visual — a packaging design, an ad creative, a shelf mock-up — gaze data and pre-verbal facial response reveal what the interview cannot. A participant can describe a product positively while gaze data shows they never fixated on the key brand element. That contradiction is the finding. 

Panel and recruitment 

ListenLabs' verified panel of 30M+ participants across 45+ countries is one of its clearest competitive advantages, particularly for hard-to-find niche audiences and rapid recruitment in short field windows.  

Decode supports bring-your-own-participant research alongside access to 103M+ profiled participants via Cint and Dynata across 120 countries. Teams that maintain their own customer panels or want to combine owned and external recruitment operate flexibly within the same platform. 

Platform breadth and method range 

ListenLabs is centered on AI-moderated interviews. It does this well and has built its product and panel infrastructure around this core use case. 

Decode spans AI-moderated interviews alongside consumer insights research, AI creative and ad testing (AI Creative Insights), usability and UX research, and a searchable repository (Insights Hub). Teams running multiple research methods — concept tests, creative pre-tests, packaging studies, and qualitative interviews — can run them all in one platform without switching tools between methods. 

Repository and knowledge reuse 

ListenLabs' Mission Control aggregates findings across studies, enabling teams to surface patterns from past research and build institutional knowledge over time. 

Decode's Insights Hub stores quantitative, qualitative, and behavioral signal data in a single searchable archive. The addition of behavioral data — emotion scores, gaze patterns, attention findings — alongside transcripts and survey responses means the repository compounds with a richer signal over time. 

Pricing

ListenLabs does not publish pricing. It is sold as a managed research engagement. Based on third-party reported estimates — which should be verified directly with ListenLabs before budgeting — enterprise engagements are reported at approximately $20,000 as an annual base, with session costs running roughly $300 to $400 per interview. These are buyer-reported figures, not confirmed pricing, and the managed model includes recruitment operations and research execution alongside the platform. 

Decode is enterprise-priced with custom contracts based on research scope, platform access, and panel sourcing.

The relevant comparison is total cost of research: platform licence, respondent sourcing, sessions, and whether the platform covers all the methods your team runs. A platform priced per session may look different across a full annual research program that includes creative testing, concept research, and usability studies alongside interviews. 

ListenLabs alternatives and competitors 

Teams evaluating ListenLabs for AI-moderated interview research typically shortlist from the following: 

• Decode by Entropik — measured emotion AI, eye tracking, and a full research stack. Best for teams that need behavioral depth and multi-method coverage beyond interviews. 

• Outset.ai — AI-moderated interview platform for product and UX research. Strong on synthesis speed. Interview-focused. 

• Conveo — enterprise AI qualitative research with video-first evidence traceability and EU data hosting. Strong for compliance-first teams. 

• Strella — AI interview platform for consumer research. Qualitative-only, fast deployment. 

• Maze — rapid prototype testing and user research for design teams. Stronger on design validation than consumer insights. 

• Dscout — mobile diary and live research. Best for longitudinal and contextual studies. 

 
The right fit depends on whether speed and panel scale are the priority, or whether behavioral depth, multi-method coverage, and compliance requirements drive the selection. 

When to choose ListenLabs vs when to choose Decode 

Choose ListenLabs when

• Speed and recruitment reach are the primary constraints — especially for fast, large-volume AI-moderated interview studies with hard-to-reach niche audiences 

• Your research program is centered on qualitative interviews with a verified panel 

• Sub-24-hour turnaround is a real operational requirement, not just a preference 

• Ekman-based emotional analysis from the interview conversation is sufficient signal depth for your decisions 

 Choose Decode when

• Your research questions require measured emotion, attention, and gaze data — not only conversation-extracted signals 

• You run multiple research methods: interviews alongside creative testing, concept testing, packaging research, or usability studies 

• Multi-market and non-English research coverage matters — 70+ languages vs. a more concentrated panel 

• You need a longer enterprise deployment record and a full behavioral measurement stack 

Neither platform is the universal choice. The decision comes down to how much your findings depend on what happens beyond the verbal response. 

How Decode helps 

The gap between what participants say and what they actually feel — the say-do gap — is the central problem that behavioral research exists to close. An interview tells you what someone said when asked. It tells you less about what triggered a reaction before they composed an answer, or where their attention went on a stimulus they were evaluating. 

Decode's AI Moderator captures the verbal layer — adaptive, probing, in 70+ languages. Facial Emotion AI, Eye Gaze Tracking, and Voice Emotion AI instrument the behavioral and emotional layers in the same session. AI Creative Insights applies the same measurement to creative pre-testing. Insights Hub stores and surfaces findings across all methods and all studies, so every research session compounds what your team knows. 

For teams whose questions go beyond what participants tell you — to what they feel, where they look, and how strongly they react — that combination is what Decode is built for. 

Frequently asked questions 

1. Is Decode a good ListenLabs alternative? 

Yes, for teams that need measured behavioral and emotional signal data (facial coding, eye tracking, attention) alongside AI-moderated interviews. Decode also covers research methods ListenLabs doesn't — creative testing, packaging research, usability studies. For teams whose primary need is fast AI-moderated interviews at large scale, ListenLabs is a strong option. 

2.  What is the main difference between Decode and ListenLabs? 

ListenLabs applies Ekman-based emotional intelligence from voice and expression cues in the interview. Decode measures facial emotion, eye gaze, and voice as dedicated research technology applied during the study. Decode also covers more research methods — creative testing, concept research, and usability in addition to qualitative interviews. 

3. Does ListenLabs have facial coding or eye tracking? 

ListenLabs applies Ekman-based emotional intelligence from conversation and expression cues. It does not offer dedicated eye gaze tracking. Decode provides both — facial coding at 90%+ accuracy tracking 62 expressions, and eye tracking at 96% accuracy. 

4. How much does ListenLabs cost? 

ListenLabs does not publish pricing. Based on third-party buyer-reported estimates, engagements are approximately $20,000 as an annual base with session costs of $300–$400 per interview. These figures are unconfirmed — verify directly with ListenLabs before budgeting. 

5. Which is better for large-scale interview studies? 

For high-volume AI-moderated interview programs with hard-to-reach audiences and sub-24-hour turnaround requirements, ListenLabs' panel scale and recruitment infrastructure are genuine advantages. For programs that also require behavioral diagnostics, creative testing, or multi-method research, Decode's broader platform is the stronger fit. 

6. Can Decode replace ListenLabs entirely? 

For most research programs, yes. Decode's AI Moderator covers AI-moderated interviews, and adds behavioral measurement and broader method coverage. The area where ListenLabs has a distinct advantage is panel scale and rapid recruitment for very large-sample qualitative programs. If that is the primary constraint, compare panel specifications directly before switching.  

The bottom line 

ListenLabs is a well-built, fast, and well-funded AI-moderated interview platform with a large verified panel and genuine emotional intelligence capabilities. It is the right choice for teams where speed and recruitment scale are the dominant requirements. 

Decode is a behavioral measurement platform that adds measured facial emotion, eye gaze tracking, and voice analysis to the interview layer — and extends the same measurement across creative testing, concept research, and usability studies in one platform. 

Choose ListenLabs if the priority is fast, large-scale AI-moderated interviews with deep panel reach. Choose Decode if decisions depend on measured behavioral and emotional evidence, multi-method coverage, and a research platform that compounds institutional knowledge over time.