This review judges Conveo on its own terms first: how fast it delivers, what it costs, how deep its interviews go, how it scales, how useful its output is, and how it handles security, with its ratings and customers alongside. A comparison with User Intuition follows. 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. Its interviews run 20–30 minutes by voice, video or chat. Every Conveo claim below is drawn from Conveo’s own site, docs, trust center or its G2 listing, and dated where it can change.
What Is Conveo?
Conveo is a Y Combinator-backed (S24) AI interview platform built around multimodal signal extraction. Founded in Antwerp in 2024, it is now headquartered in New York with engineering in Belgium, and on September 2, 2026 it announced a $50M Series A (total funding $55.8M) to fund U.S. expansion. Conveo says more than 400 enterprises use it, including over 50 Fortune 500 brands, and positions itself as consumer understanding infrastructure for enterprise insights and brand teams.
Its interviews are AI-moderated voice or video conversations that participants take on their own time, with the AI asking follow-ups after each answer, and signal flows out of every interview through words, vocal tone, facial expressions, gestures, and objects in view. Conveo has no first-party panel: it says it works with 8+ panel providers — Respondent and User Interviews are API-integrated, and bespoke partners such as Norstat, Bilendi, Sago, Rakuten, DataDiggers, and NewtonX quote per project — plus BYOC paths via CSV upload, external panels, QR codes, and WhatsApp invites. Conveo says it supports 50+ interview languages, with multi-market global benchmarking framed as a core use case.
Conveo is particularly relevant when the research design combines interviews with structured methods such as MaxDiff. Researchers define the options, choose follow-up settings and collect explanations alongside rankings. Its voice and video analysis adds recorded reactions to the material available for interpretation. These capabilities fit briefs that already have concepts, messages or prices to compare.
Structured testing and supporting reactions. Conveo supports MaxDiff, Van Westendorp and Gabor-Granger pricing questions (changelog), quotas, routing and monadic stimulus rotation alongside open-ended conversation. Its video analysis adds facial and vocal cues to the participant’s words. The researcher still has to explain what those observations mean for the decision. User Intuition emphasizes adaptive laddering to uncover the needs and trade-offs that should shape the options in the first place, then evidence coverage to assess the explanation. Discovery interviews can therefore inform a later structured test. This review covers speed, cost, depth, scale and the usefulness of findings, followed by security and evaluation questions.
How Fast Does Conveo Deliver Results?
Conveo’s delivery clock is shaped by two forces pulling in opposite directions. The self-scheduled format compresses the participant side dramatically — there are no live calendars to align, no moderator schedules to chase, no time-zone juggling across geographies. Participants take the interview when it suits them, 24/7, answering each AI follow-up in turn, and responses flow into the multimodal analysis layer as they land; Conveo states a fielding speed of 100 interviews in 3 days. The countervailing force is the procurement side: a sales-led demo, Enterprise contracting, and recruitment setup with panel providers set the runway before any interview gets fielded.
End-to-end question-to-answer time falls into three regimes, set by where a buyer stands when the research question arrives.
Established Conveo Enterprise account with recruitment in place: Conveo’s own claim is 100 interviews fielded in 3 days, plus setup and analysis time. Study setup runs in parallel with recruitment through whichever panel provider fits the audience profile, self-scheduled sessions field over several days, and the multimodal synthesis layer produces extracted themes against the recorded corpus. The credit is already prepaid and the panel relationships are settled, so the bottleneck is fielding velocity rather than setup overhead.
Pay & Go agency project: set by recruitment and scope. Pay & Go has no annual commitment, and access still starts with a demo; bespoke partner panels quote per project, while the API-integrated panels start fielding once an engagement is posted. Agencies running recurring Pay & Go cycles against a stable audience footprint compress this; one-off projects against unfamiliar geographies extend it.
New Enterprise buyer, no contract: time to start depends on a sales-led onboarding, since Conveo has no self-serve sign-up, and Conveo publishes no typical duration. Demo, scoping, procurement, recruitment setup, and credit sizing all stack ahead of the first study, with the first interview waiting on the last of those to clear. For its always-on StoryLines programs, Conveo says most teams are live with their market within a couple of weeks.
When the speed model fits. Established Enterprise accounts running continuous multi-market concept testing or benchmarking research where panel partner relationships are settled and the credit pool is sized to the team’s actual cadence. The format’s compression of the participant clock translates into real velocity once the procurement clock has already been spent.
What Does Conveo Cost?
Conveo publishes no pricing for its interview platform, account sign-ups are disabled, and its G2 pricing page says there is no free trial. Its G2 listing shows vendor-supplied pricing, last updated March 18, 2026, with a dual-tier structure.
The first edition, Pay & Go, sells credits as needed at a higher per-credit price and leaves out enterprise features; per its G2 notes, Conveo aims it at agencies and small enterprises without a recurring research need, does not publish its rates, and still starts activation with a demo. The second, Enterprise, starts at $45,000 per year, prepaid annually, at Conveo’s lowest per-credit price. Billing on both runs from a USD credit balance, per Conveo’s billing docs: analysis is charged per interview minute at a base rate, enabled features such as advanced video analysis multiply that rate, and each recruitment provider bills separately. Conveo sells to enterprise insights and brand teams, including always-on programs, and current pricing and inclusions come from a scoped quote.
For cost by research frequency at 1, 5, 10, 20, and 50 studies per year, what a prepaid credit does to effective per-study cost at different cadences, and the line items to request in a quote, see the Conveo pricing breakdown.
Already evaluating Conveo? Run the same research question on User Intuition first — three free voice interviews with your own participants, no card, five-minute setup. Start free →
How Deep Does Conveo Go in Each Interview?
Depth on Conveo is a researcher setting. The topic guide sets a follow-up budget per question — automatic probing (0-5 follow-ups), none, 0-1, 1-2, or 2-5 — and the multimodal-signal-extraction architecture then shapes what gets captured, what gets analyzed, and what shape the resulting evidence takes.
Moderator behavior. The AI moderator runs the researcher’s topic guide in turns: the participant records a spoken answer, on camera or with the camera off, and the AI asks follow-ups based on that answer, within the follow-up budget set for each question. Researchers also pick the moderator’s tone and can write probing instructions, and guides can mix open-ended spoken questions with select, open-text, MaxDiff, and pricing questions. Conveo claims over 70% of final insights come from these AI-driven follow-ups. Inside each response, the signal extraction layer captures words, vocal tone, and facial cues. The question to test is how deep the follow-ups go at the budget you set — up to five per question — compared with laddering that runs 5-7 levels by default.
Interpreting recorded reactions. Conveo combines words, vocal tone and facial cues in its analysis. A reaction to a concept can give the researcher a useful moment to inspect in the recording and discuss alongside the participant’s explanation. Conveo’s own emotional-analysis docs say these readings do not prove what a participant felt or that a stimulus caused an emotion. For a question such as why a buyer rejected the concept, the follow-up conversation matters: what experience shaped that response, what benefit was missing, and what trade-off would change the choice? User Intuition’s laddering is designed to develop that explanation through connected follow-ups, while evidence coverage helps researchers assess whether it is sufficiently supported to guide the recommendation.
Synthesis behavior. Themes combine the multi-signal evidence into output that pairs extracted theme statements with the multimodal video clips that support them. The output shape suits concept-validation deliverables and stakeholder communication: a stakeholder watching a packaging-reaction clip with the platform’s tonal-shift annotation can see and hear the evidence at once, which lands well in presentation contexts and brand-side decision meetings. Conveo says every insight links back to its source data and is tagged to its source video clip, and its click-through charts go from statistics to verbatim quotes, so a synthesized claim can be checked against what a participant said.
When depth is Conveo’s strength. Concept testing, creative validation, and multi-market benchmarking where multimodal signal extraction surfaces what verbal response hides. The decision space is “does this resonate emotionally” — does the ad land, does the packaging variant trigger the intended response, does the positioning feel right across faces in three markets — and the platform’s signal layer is purpose-built for that question.
How Does Conveo Scale to Your Research Volume?
Conveo’s scaling shape is determined by three architectural pieces fitting together: the partner-panel network, BYOC recruitment, and the Enterprise credit-bundle commercial model.
Audience scaling. Conveo is panel-agnostic by design: it runs no panel of its own and says it works with 8+ panel providers. Two of them are wired in over API, so an engagement posted to Respondent (a 3M+ panel with B2B coverage across 150 industries) or User Interviews starts fielding; Norstat, Sago, Bilendi, Rakuten, DataDiggers and NewtonX quote over chat, and healthcare panels (Sermo, M3, Reckner, Rare Patient Voice) are marked coming soon. Decipher (Forsta Surveys) and Rally are software integrations, not panels. BYOC supplements the partners with CSV upload, external panel feeds, QR-code distribution, and WhatsApp invites. For consumer benchmarking that needs reach across several markets in the same study, the partner network is broad. The recruitment economics deserve a scoping question — Conveo does not sell recruitment, so costs pass through per provider (plus a commission on integrated panels), and the provider mix materially changes the all-in cost of a multi-market study.
Frequency scaling. The Enterprise tier is prepaid annually and starts at $45,000/year. That prepayment amortizes well when research cadence is continuous and high — twenty-plus studies in a year at Conveo’s lowest per-credit price produces favorable effective per-study economics, and Conveo’s StoryLines product runs always-on programs, with one large tech company running about 2,000 interviews a month on it, per Conveo. The same prepayment amortizes poorly at low cadence: a team running three studies in a year against a $45K+ Enterprise commitment pays a much higher effective per-study cost, so ask how unused credits are treated at year-end. Pay & Go exists for agencies and smaller teams that don’t want the annual commitment, at a higher per-credit price than Enterprise.
Team scaling. Procurement-driven, with Enterprise contracts and PAYG accounts both starting with a sales demo rather than self-serve account creation. The dual-tier model creates a different entry point for agencies (PAYG) than for enterprises (Enterprise contract), but neither path looks like the distributed-self-serve model where product managers, marketing leads, and CX directors spin up their own studies inside an existing seat. The platform’s center of gravity is research-led procurement, not horizontal-distribution adoption across non-research functions.
When scale is Conveo’s strength. Enterprise multi-market benchmarking practices running continuous concept testing or creative validation research where Conveo’s partner-panel network covers the audience reach and the prepaid credit gets used across consistent annual volume.
How Useful Are Conveo’s Insights — and Do They Compound?
Conveo’s per-study output is a synthesized theme set paired with the multimodal video clips that support each theme, plus reports, slides, quote reels, and click-through charts. The question worth asking is whether that output compounds — whether the third study learns from the second and the first.
Per-project insight quality. Conveo links themes to recorded responses and participant clips, giving a research team material it can inspect and use in a concept readout. Structured choices and the explanations behind them can be presented together. The quality of the recommendation depends on how those accounts answer the brief, the sample represented, and the interpretation the researchers bring to the evidence.
Insight compounding. Conveo sells a cross-study knowledge layer. Its Talk to Your Data assistant can explore one study, compare selected studies, or query a whole project or StoryLines program in plain language, citing participant evidence, and Conveo markets the result as a research library where insights compound across projects. Both Conveo and User Intuition offer cross-study, natural-language querying of past research.
Concrete example: if January’s concept test surfaced positive facial reactions to a packaging variant, and March’s brand benchmark captured tonal confidence about the same brand, ask Talk to Your Data “do positively-reacting concept-test participants show different brand confidence in subsequent benchmark waves” across both studies in a pilot, and judge the answer against the cited evidence. For longitudinal questions, StoryLines runs the same core questions weekly, bi-weekly, or monthly, with trend charts for each wave.
When the insight model works. Concept-validation and benchmarking programs where the multimodal-evidence package is the artifact the stakeholder consumes, with a queryable library behind it. The output earns its keep inside each study and, through Talk to Your Data and StoryLines, across studies.
How Does User Intuition Differ from Conveo?
User Intuition differs from Conveo in three ways that hold up against Conveo’s own documentation; the Conveo vs User Intuition comparison sets them side by side.
- Depth by default. Conveo’s researcher sets a follow-up budget per question, up to five. User Intuition’s 20–30 minute interviews ladder 5–7 levels by default, and you decide how far the moderator probes around required questions pinned in your wording.
- A vetted first-party panel. Conveo says it is not a panel provider and recruits through partners such as Respondent and User Interviews, billed separately. User Intuition recruits from its own 4M+ vetted panel across 58 countries, where our team reviews a video identity interview with every prospective panelist before accepting them, screens every session for AI-generated or coached answers, and still accepts your own sample.
- Published, quality-only pricing. Conveo starts with a demo and bills credits per interview minute. User Intuition publishes $30 per quality voice interview with no subscription and does not charge for interviews that fail quality checks.
The design commitments differ too. Conveo reads what shows up across signal types in each response; User Intuition follows the why through systematic laddering, from concrete behaviors through functional benefits to emotional drivers and personal priorities. Both questions matter, and they lead to different platforms. The subsections below compare the two on the same five dimensions used for Conveo above.
Speed
User Intuition starts with five-minute self-serve setup and three free voice interviews with your own participants. Standard panel recruitment is available separately. Panel studies return 200+ interviews in 24 hours; with your own participants, interviews run in parallel as they respond, without a platform-imposed hourly cap.
The two clocks start in different places. Conveo’s starts with a demo and, for a new buyer, a contract; User Intuition’s starts with a self-serve account. A buyer evaluating both this week can compare procurement-call schedules against a working set of three interviews already returning themes. For multi-market benchmarking inside an established Enterprise relationship, Conveo’s compression of the participant clock is real and valuable; for time to a first finding, the gap between a demo-led start and a same-day self-serve start is real, and Conveo’s claimed fielding speed of 100 interviews in 3 days is a separate question.
Cost
Where Conveo’s Enterprise tier starts at $45,000/yr, prepaid (or Pay & Go credits at unpublished rates), User Intuition publishes per-study pricing that scales linearly with research cadence. Quality voice interviews run $30 each, with studies starting at $150 for five quality voice interviews with your own participants. No annual base, no seat fees, no procurement floor; recruitment priced separately.
The operating-model difference shows at the Enterprise floor: Conveo’s prepayment is committed before the year’s research runs, while User Intuition spend follows the studies the team chooses to fund. Which model fits depends on what the research deliverable is. If multimodal signal extraction across multiple partner-panel markets is the artifact, the prepaid credit funds the analysis, recruitment is billed on top, and the Enterprise floor is the price of access. If motivational depth via adaptive laddering is the artifact, a prepaid floor buys access that goes unused at low cadence, and per-interview billing lets spend follow the studies you run.
Depth
Where Conveo’s depth runs through multimodal signal extraction — the what across voice, video, tone, facial, emotional, and contextual modalities at the moment of response, plus follow-ups within a researcher-set budget of up to five per question — User Intuition’s depth runs through adaptive 5-7 level laddering — the why underneath the pattern, surfaced through adaptive follow-up questions across each interview.
These are different optimization targets, not better-versus-worse outcomes. Conveo answers “did this resonate emotionally” by reading the reaction signal across modalities. User Intuition answers “why does this resonate emotionally” by laddering, informed by Reynolds and Gutman (1988), from the participant’s concrete behavior toward the functional benefit it produces, then toward the emotional consequence of that benefit, then toward the underlying value the emotional consequence connects to, then back to verify the connection holds. The AI moderator adapts in flight — when an answer is shallow, it probes; when a participant stalls, it redirects; when a thread is more interesting than the next planned question, it follows the thread before returning to the guide.
Both methodologies are real and distinct. For concept testing where a face during stimulus reveals more than a verbal response after stimulus, multimodal extraction is the right shape. For motivational research where the question is the reason of a behavior — why customers churn, why positioning fails, what brand value drivers predict purchase — adaptive laddering across one signal type reaches what extraction across modalities at one point in time does not, and Conveo’s follow-ups probe toward it within the budget the researcher sets (up to five per question).
Scale
Where Conveo’s scale runs through third-party panel providers (8+, per Conveo) plus BYOC — broad multi-source recruitment billed per provider — User Intuition’s scale runs through a first-party 4M+ vetted panel across 58 countries available in every account plus native CRM recruitment of your own customers in the same workflow.
Both architectures are real options for different audience profiles. The Conveo footprint reaches geographies and specialized audiences that no single panel covers, which earns its keep when the audience profile is multi-market consumer benchmarking or specialized B2B segments distributed across the partner stack. The User Intuition footprint includes the panel as table-stakes and adds your-own-customers recruitment via HubSpot integration (Salesforce and Pipedrive via Zapier) without a separate tool or partner conversation. Hybrid studies — panel plus your customers in the same research workflow — run natively. For audience profiles that map to “panel-reachable consumers or our own customer base,” the integrated panel access plus CRM-native recruitment is the simpler operating model. For audience profiles that require several panel providers’ worth of geographic and segment reach, Conveo’s network is the broader one.
Insights
Where Conveo’s insight output pairs multimodal video clips with extracted themes, queryable across studies through Talk to Your Data, User Intuition’s insight output flows into the Customer Intelligence Hub, a searchable body of research queryable in plain language across every study the team has ever run.
The structure of that compounding is the difference to test in a pilot. Conveo’s Talk to Your Data reads across the studies, projects or StoryLines programs a researcher selects and cites participant evidence in its answers. User Intuition parses each interview against one ontology when it completes, so a theme coded in a churn study and the same theme surfacing in a later positioning study land on the same node without a researcher mapping them by hand. To compare the two fairly, load two related past studies into each platform and ask one cross-study question whose answer you already know; then check which answer cites the right participants and which misses a study.
Both platforms query past research in plain language; the difference is structure. User Intuition indexes every interview against one ontology, so themes, codes, and quotes line up across studies by default.
Both platforms link findings to source evidence, so traceability is not the difference. The difference is a sufficiency check: User Intuition’s evidence coverage, informed by Malterud’s information power and Hennink’s meaning saturation, reports for each learning goal whether the interviews hold enough relevant, varied detail to support a recommendation, and names the missing experience when they do not. Both platforms also expose an API and an MCP server; in User Intuition, the API and MCP workflow lets an assistant turn that gap into a costed study plan for a researcher to approve.
Side-by-side at a glance
| Dimension | Conveo | User Intuition |
|---|---|---|
| Speed | Conveo claims 100 interviews fielded in 3 days; sales-led onboarding for new buyers | 200+ panel interviews in 24 hours; five-minute self-serve setup |
| Cost | Enterprise from $45K/yr prepaid; Pay & Go credits (rates not published) | $30 per quality voice interview, $150/5-interview study |
| Depth | Researcher-set follow-ups (up to 5 per question) + multimodal signal extraction (the what) | Adaptive 5-7 level laddering (the why) |
| Scale (audience) | Third-party panel providers (8+, per Conveo) + BYOC; no first-party panel | 4M+ vetted panel (58 countries) + CRM-native |
| Scale (frequency) | Enterprise credit pool against annual floor; Pay & Go credits | Linear per-study, no floor |
| Scale (team) | Procurement-routed | Self-serve plus enterprise procurement |
| Insights (quality) | Multimodal video clips + extracted themes | Themed transcripts with depth on needs and trade-offs |
| Insights (persistence) | Cross-study queries via Talk to Your Data; research library | Ontology-indexed Customer Intelligence Hub |
| Public ratings | 4.4/5 on G2 (13 reviews); 0 Capterra reviews (September 26, 2026) | 4.9/5 on G2 (5 reviews); 5.0 on Capterra (3 reviews) |
| Free trial | None per G2 and Capterra; demo-led | 3 free voice interviews with your own participants on signup, no card |
What Do Ratings and Customers Say About Conveo?
Conveo’s public review footprint is small. As of September 26, 2026, its G2 rating is 4.4 out of 5 from 13 reviews, and Capterra lists no user reviews. Both vendors’ public review counts are small (13 on G2 for Conveo; 5 on G2 and 3 on Capterra for User Intuition), so reference calls carry more weight than either rating.
The customer list is the stronger signal. Conveo says more than 400 enterprises use it, including over 50 Fortune 500 brands, and it names Google, Unilever, AB InBev and Canva. Its co-founders are Dieter De Mesmaeker, previously founder and CTO of DataCamp, and Hendrik Van Hove, formerly at McKinsey & Company, and its head of research and methods, Niels Schillewaert, is a former ESOMAR president. On the participant side, Conveo’s media kit says 97% of participants rated its AI-moderated interview experience positively and 25% said it felt similar to a human interviewer; that is Conveo’s own published research.
For a buyer, the practical reading is that Conveo is well funded, enterprise-led and early in public reviews. Ask for two references with a brief like yours, one on Pay & Go and one on Enterprise, and ask each how many follow-ups their guides use and what recruitment cost per participant.
How Do Conveo and User Intuition Compare on Security and Compliance Posture?
Conveo publishes the more complete certification set today; User Intuition adds agency-specific delivery controls. Conveo’s trust center lists SOC 2 Type II, SOC 3, ISO 27001:2022, ISO 27701:2019 and GDPR, a 2026 penetration test, core hosting on AWS in the EU, and isolated deployments with dedicated models for enterprise clients; it does not list HIPAA. Conveo says it does not train AI models on client or agency data. User Intuition is GDPR & CCPA compliant and SOC 2 Type II compliant, never trains AI models on customer data, keeps unreleased stimulus confidential, and isolates each client’s studies in its own workspace. If an ISO certificate is a hard procurement gate, Conveo clears it today.
Security review should follow the actual study data: participant identifiers, recordings, transcripts, access, retention, subprocessors, and permitted reuse. Use Conveo’s current trust documentation and User Intuition’s security overview for the applicable reports and controls.
For a customer-list study, document who may contact the participants and who can access their responses. For panel research, establish which recruiting provider handles identifying information and what reaches the research workspace. For agencies, confirm client access and separation alongside any required SSO or contractual controls. Keep these requirements in the procurement decision alongside interview method, cost, and evidence quality.
Why Do Research Teams and Agencies Choose User Intuition Over Conveo?
Judged as research tools rather than as vendors, the two platforms reward different briefs, and the teams that pick User Intuition weigh the same things in the same order. The explanation comes first: laddering 5–7 levels by default reaches the needs and trade-offs behind a choice in every interview, where Conveo’s depth follows the follow-up budget set for each question. The method comes second: pinned verbatim questions, study rules such as no PII or no product claims, screeners, hard quotas, and monadic or sequential monadic cells compared side by side, as described on AI-moderated in-depth interviews. Third is whether the respondents and the evidence survive review: a 4M+ vetted panel with every voice interview screened for AI-generated or coached answers, or a team’s own sample from Prolific, Cint / Lucid, CloudResearch, a customer list or any provider via custom link, with every finding traced to its quote, transcript and recording. Format and reach come fourth: voice, video or chat interviews in 80+ languages, where Conveo states 50+. Price is weighed last, and it is the easy part to verify: the per-interview rate is on the website, there is no subscription, and interviews that fail quality checks are not billed. Agencies add isolated per-client workspaces, an editable presentation and CSV exports, as shown on the agency research page. Carevoices, a healthcare and pharma research agency, is one example: it runs User Intuition through the API from study creation to analysis, finished a fixed-price primary- and urgent-care study in under two weeks, and reports more than triple the number of studies it can run at once (case study).
How to Choose Between Conveo and User Intuition
Start with the decision your research must support. Choose Conveo if the deliverable is a MaxDiff, Van Westendorp or Gabor-Granger result with spoken explanations, facial and vocal coding of reactions to video, or an always-on tracking program on prepaid annual credit, or if procurement requires ISO 27001 or ISO 27701 certification today. User Intuition fits teams that need the reason behind a decision: 5–7 levels of laddering by default on their own guide, a vetted panel and evidence coverage, priced per quality interview. The two can work in sequence when discovery needs to shape the options for a structured test.
Research question × methodology fit
| Research question | Best fit | Reason |
|---|---|---|
| Ranking defined concept benefits and hearing the reasons | Conveo | MaxDiff can combine structured choices with interview explanations |
| Creative validation across multi-market consumer segments | Conveo | Partner-panel network reaches the geographies; extraction layer reads reaction |
| Churn motivation, why-customers-leave research | User Intuition | Adaptive laddering reaches the needs and trade-offs behind the behavior |
| Brand positioning and customer priorities | User Intuition | Laddering surfaces the needs and trade-offs that shape loyalty |
| Win-loss research with deep buyer reasoning | User Intuition | Systematic probing across each decision factor reaches the why behind the choice |
Research-frequency fit
| Annual cadence | Best fit | Reason |
|---|---|---|
| 1-3 studies/year, variable cadence | User Intuition | Per-study pricing with no annual floor; $45K+ Conveo Enterprise floor amortizes poorly here |
| 5-15 studies/year, growing program | User Intuition | Linear scaling without contract re-scoping at every cadence change |
| 20+ studies/year, established continuous program | Either | Conveo Enterprise credit pool amortizes; UI per-study scales linearly — methodological fit decides |
Operating-model fit
| Operating model | Best fit | Reason |
|---|---|---|
| Trying the platform before any procurement step | User Intuition | Three free voice interviews with your own participants at signup; no card or sales call |
| Insights teams or agencies running research per project or per client, plus product, marketing and CX teams | User Intuition | Per-study pricing, isolated per-client workspaces and self-serve setup let each team run studies without a platform contract |
| Enterprise-procurement-led consumer insights practice | Conveo | Enterprise contract maps to the operating context |
| Fixed-fee agency projects priced before the pitch | User Intuition | Published per-interview rate goes into the proposal the same day; failed interviews are not billed; isolated client workspaces |
| Agency briefs whose deliverable is a MaxDiff or pricing result, or facial coding | Conveo (Pay & Go) | Conveo aims Pay & Go at agencies; rates are quoted after a demo |
Using both in sequence. A team can use User Intuition to investigate why a concept matters, refine the benefits and assess unresolved questions, then use Conveo for a MaxDiff ranking of the resulting options. When the project only needs discovery interviews and a recommendation traced to the verbatim, User Intuition provides that workflow with published project pricing. Add a structured test when it serves the decision.
Evaluation Questions for Your Conveo Demo
Use these questions in the scoping call before committing to an Enterprise contract or PAYG engagement.
Speed
- From signed Enterprise contract to first production study running, what’s the typical runway including panel access setup and credit-pool sizing?
- On PAYG, how does engagement-to-engagement scoping affect the front-end clock for an agency running quarterly cycles?
Cost
- How does the credit pool work — what counts against minutes (interview duration only, or includes processing and synthesis), what happens to unused credits at year-end, and how is overage priced relative to contract per-minute rates?
- What will recruitment cost per participant for our audiences through each panel provider, and what commission applies on the integrated panels?
Depth
- For research where the deliverable is motivational themes rather than multimodal video clips, how does Conveo’s analysis layer compare to native-AI peers built around systematic adaptive laddering on every conversation?
- When a participant says something unexpected, how many follow-ups does the AI moderator ask at each follow-up budget setting, and how deep do they go? Show three example sessions at the 2-5 setting.
Scale
- For multi-market benchmarking across France, Germany, and the UK on the same protocol, which of your panel providers fields each market and what’s the cost variance across them?
- For BYOC recruitment via CSV or WhatsApp, how does signal-quality control compare to integrated-partner recruitment?
Insights
- How does Talk to Your Data handle cross-study questions — across which studies, projects, or StoryLines programs, and with what evidence citations?
- Walk through three concrete examples where the multimodal signal extraction surfaced something a verbal-response reading would have missed.
Security
- Your trust center lists SOC 2 Type II and ISO 27001:2022; how can a procurement team access the most recent audit reports?
- What are the retention defaults on participant audio, transcripts, and multimodal extraction outputs, and how does your no-training policy on client data apply to your LLM sub-processors?
- For European audiences sourced via integrated panel partners, what’s the GDPR data-flow architecture across each panel-provider relationship?
Run these questions in parallel against three free User Intuition interviews. Comparative output is the cheapest way to know which model fits your team.