Sources: strella.io (product positioning, customer roster, comparison pages, changelog; checked September 26, 2026) · Strella trust center (compliance posture) · G2 + Capterra listings · buyer-reported per-study cost (2026; Strella publishes no prices). Pricing detail: Strella pricing breakdown.
What Is Strella?
Strella is an AI-moderated qualitative research platform built around real-time, voice-to-voice interviews. Researchers design a discussion guide; the AI moderator runs the conversation by voice and asks dynamic follow-ups, and researchers can switch on webcam and desktop screen recording in study settings. Strella also runs human-led (beta) and hybrid studies. The platform analyzes interviews as they complete and auto-generates highlight reels packaged for stakeholder communication. Founded in 2023 and based in New York, Strella has raised $18M, most recently a $14M Series A led by Bessemer Venture Partners in October 2025, and names Amazon, Duolingo, Apollo GraphQL, and Chobani as customers.
Architecturally, Strella sits in the same category as platforms like User Intuition, Listen Labs, and Outset: AI moderation runs the interviews; researchers own the guide and interpretation, with automated transcription, AI synthesis, and report generation in support. The differentiator Strella itself emphasizes is voice-to-voice conversation with real-time analysis: a voice moderator working at a follow-up depth the researcher sets, paired with analysis that runs as interviews complete and stakeholder-ready highlight reels.
The voice-to-voice interview and real-time synthesis. The most useful concept for understanding Strella as a buyer is how its interview format and its analysis fit together. Participants talk with an AI moderator in a real-time, voice-to-voice conversation that Strella positions against text-based and start-stop formats, on desktop or through its iOS and Android app. The moderator asks dynamic follow-ups; the researcher sets a project-wide default follow-up depth and can lock questions to exact wording. Interviews are analyzed as they complete, backed by verbatims and highlight clips, and auto-generated highlight reels package the findings for stakeholder communication. The trade-off to evaluate is depth control: follow-up depth is a researcher setting rather than laddering by default, so how far each conversation reaches toward motivation depends on the guide and settings. Setup has also moved toward guided flows, with AI-guided project setup added in January 2026.
What Are Strella’s Strengths and Limits?
Strella’s profile is clearest as a list. Each item below traces to Strella’s own pages, changelog or listings as of September 26, 2026.
Strengths:
- Live voice moderation with human options. Real-time voice-to-voice interviews, plus human-led (beta) and hybrid studies on the same platform.
- Usability tooling. Journey maps, usability heatmaps and task analytics, with automatic pass/fail task grading (June 2026) and card sort studies (July 2026).
- Controls for regulated work. Participant anonymization (March 2026), automatic MNPI checks for regulated industries (May 2026) and audit logs (June 2026).
- Fast, packaged analysis. Interviews are analyzed as they complete, with auto-generated highlight reels, a searchable repository and an MCP-based AI Connector.
- A full-service option. Strella Advisory runs scoping, research and synthesis, and pitches commercial due diligence for mid-market private equity as 30+ expert interviews in 10 days.
Limits:
- Depth is a setting. Follow-ups run to a project-wide depth the researcher configures, and Strella publishes no level count.
- No first-party panel. Recruitment runs through partner panels (Respondent and User Interviews), expert networks and your own lists.
- No published price or public sign-up. Buying starts with a demo and a quote-based annual plan.
- Language coverage. 46+ interview languages.
- Security detail. Strella states SOC 2 and GDPR adherence but no SOC 2 type publicly.
How Fast Does Strella Deliver Results?
Strella markets real-time synthesis: interviews are analyzed as they complete, backed by verbatims and highlight clips, with auto-generated highlight reels packaged for stakeholders. Its homepage promise is “100 customer interviews by tomorrow morning.” In AI-moderated studies, fielding does not wait on a human moderator’s calendar. The product manager scenario the marketing implies: launch one day, read themes the next, and take the customer voice into the sprint review.
The clock that decides procurement is wider than the in-study window. Real-time synthesis only starts after the buying path: Strella is sales-led, with a demo, a custom quote on an annual plan, and no public sign-up, before recruitment through partner panels or your own list begins. An established account already on a plan skips the buying stages on its next study. A new buyer does not, and Strella publishes no typical time from first call to first study, so ask for it in the demo.
End-to-end question-to-answer time:
- Established Strella account, panel-reachable audience: recruitment + fielding + analysis as interviews complete (Strella markets 100 interviews by the next morning)
- New buyer, new audience: sales cycle (demo + quote + annual plan) + recruitment + fielding + analysis; Strella publishes no typical duration
When the speed model fits. Teams already on a Strella plan whose research input has to land inside the current sprint window to change the decision being made. Once the buying path is behind them, Strella shortens each clock inside the study — AI moderation for the participant clock, integrated partner panels for the recruitment clock, analysis as interviews complete for the analysis clock, auto-generated reels for the stakeholder-communication clock. For teams paying for stakeholder communication delivered reliably inside an annual plan, the plan maps to the value being delivered.
What Does Strella Cost?
Strella publishes no price on its website; strella.io/pricing redirects to the homepage, and every prospect goes through a demo-first sales motion. As of September 2026, Strella sells annual plans priced on company size, needs, and research usage, which it describes as usage-based, with no per-seat charges and no large minimums; the plans can scale from one team to a full enterprise rollout. Buyers report roughly $10K-25K+ per study; Strella does not publish that figure, so treat it as a planning range and confirm it in a quote. Since January 2026, recruitment fees and participant incentives are paid from prepaid credits on a Billing page. There is no published free trial, and the app offers sign-in only. The plan underwrites what the marketing emphasizes: voice-to-voice AI moderation, analysis as interviews complete, auto-generated highlight reels, and a research repository with AI Chat. Strella also sells Strella Advisory, a separate full-service option. The plan components, and what to confirm in a quote at 1, 5, 10, 20, and 50 studies per year, are laid out in the Strella pricing breakdown.
Reading this before a Strella demo? Bring one live research question to the demo, and field the same question as three free User Intuition voice interviews with your own participants, so the review below can be checked against transcripts. Start free →
How Deep Does Strella Go in Each Interview?
Two choices shape depth in Strella: a real-time voice-to-voice interview format and a follow-up depth the researcher configures. Together they decide what questions a given study can credibly answer.
Moderator behavior. The AI moderator runs the discussion guide as a real-time, voice-to-voice conversation and asks dynamic follow-ups based on each answer. Researchers set a project-wide default for follow-up depth, tune the moderator’s reaction length and response speed, add global moderator guidance, and choose Strict mode, which reads questions exactly as written, or Adaptive mode, which allows minor rephrasing. Bessemer reports the voice moderator can sustain conversations of up to 90 minutes. The trade-off sits at the probing layer: depth follows the researcher’s settings rather than laddering by default. When a participant volunteers something unexpected, gives an ambiguous answer, or stalls mid-thought, how the moderator follows up matters more than how cleanly it runs the script. That follow-up depth is the single most important thing to evaluate against your own discussion guide during a Strella pilot.
Synthesis behavior. Strella analyzes interviews against the study’s objectives as they complete, backed by verbatims and highlight clips, and since August 2026 automatically codes open-ended answers into categories; AI Chat then generates charts and reports on request. For reaction research — concept reactions, ad evaluation, packaging variations, message testing — that objective-based synthesis fits because the decision space is narrow. For motivational research — win-loss diagnostics, churn driver analysis, brand identity, founder discovery — the question being asked is why, and synthesis can only surface what the interviews reached. The systematic 5-7 level laddering that reaches the why is a moderation method, not a synthesis feature, so test the depth of Strella’s transcripts at your configured follow-up setting.
When depth is Strella’s strength. Studies where the researcher knows how deep each topic needs to go and configures it — concept reactions, ad reads, message tests, usability tasks with task analytics — and wants voice conversations with highlight reels as the evidence. The research question is set by the guide, and the configured follow-up depth answers it.
How Does Strella Scale to Your Research Volume?
Three scaling axes matter for any AI-moderated platform, and Strella’s profile on each is shaped by two commercial choices: recruitment through integrated partner panels and a quote-based annual plan.
Audience scaling. Strella recruits through partner panels integrated in the product — it names Respondent and User Interviews — marketed as access to up to 8M participants, plus integrated expert networks for hard-to-reach professionals and bring-your-own participants, across 46+ languages. That is a reasonable footprint for consumer and B2B research in major markets. For panel-reachable audiences (SaaS buyers in named verticals, consumers in your product category, your own customers invited directly), the partner panels and your own lists are sufficient. The reach ceiling is the panel boundary itself: named-account research (specific Fortune 100 CIOs by name), rare clinical populations (prevalence under 1 in 10,000), and recruits that depend on warm introductions sit outside what panel-based recruiting fields reliably. Outside that lane, specialist recruiters and managed recruitment services are the fit; Listen Labs, for example, offers managed recruitment for niche, low-incidence audiences.
Frequency scaling. Strella’s annual plans are priced on company size, needs, and research usage, which Strella describes as usage-based with no per-seat charges and no large minimums, and they scale from one team to a full enterprise rollout. Recruitment fees and incentives are paid per study from prepaid credits. Strella publishes no rates. Buyers report roughly $10K-25K+ per study, a figure Strella has not confirmed; the annual quote sets the actual figure for your usage. (What to confirm at each volume is in the pricing breakdown.) The planning question is whether your research usage is predictable enough to size an annual plan a year ahead.
Team scaling. The buying motion is built around one annual plan, with Strella positioning itself as a research partner rather than a self-serve vendor. A demo, a quote, and an annual plan do not decompose into “any team member launches a study without involving the plan owner,” although plans can scale from one team to a full enterprise rollout and carry no per-seat charges. Adding 4-5 people across product, marketing, and CX who each want to run independent studies runs through the team that holds the plan.
When scale is Strella’s strength. Teams running a forecastable research program on an annual plan against panel-reachable audiences. The partner panels cover the audience, real-time synthesis matches the sprint cadence, and a usage-based annual plan fits when the team can size a year of research ahead.
How Useful Are Strella’s Insights — and Do They Compound?
Strella optimizes the per-study deliverable shape end-to-end: analysis as interviews complete, auto-generated highlight reels for stakeholder communication, and transcripts available for spot-check. The architectural question — and the one that decides whether the platform fits a continuous research practice — is how findings are stored and queried after each study closes.
Per-project insight quality. The output shape is built for stakeholder audiences. Interviews are analyzed as they complete, highlight reels are auto-generated, reports download as PDF or Word, and tables export to Excel, packaged for hand-off into the next sprint review without intermediate prep work. For research teams that consume insight as periodic per-study deliverables on the cadence of an agile sprint, this is the right shape. Presentation-ready highlight reels are one of Strella’s headline outputs. One thing to check in the deliverable: Strella says its analysis is backed by verbatims and highlight clips, so confirm in a pilot how quickly a synthesized claim traces back to exactly what a participant said when a stakeholder challenges it.
Insight compounding. Strella keeps a research repository that stores AI-moderated and human-moderated interviews, and its AI Chat can query a single session or the full repository. Since March 2026, its MCP-based AI Connector also lets customers query past research from Claude, ChatGPT, and other MCP clients. So Strella does offer cross-study querying; the question is how the knowledge is structured.
Concretely: if January’s brand health study surfaced that customers value durability over price, and March’s churn analysis surfaced that churners cited cost as their stated reason, ask Strella’s AI Chat “do durability-valuing customers churn for cost reasons, or different reasons” against the full repository in a pilot, and judge whether the answer holds up against the transcripts. Run the same test on User Intuition’s Customer Intelligence Hub, which indexes every interview against one ontology so themes, codes, and quotes line up across studies.
When the insight model works. Periodic deliverables for sprint-cycle stakeholder audiences where the highlight reel is the asset, backed by a repository the team can search later. Research operating models where per-study delivery and stakeholder packaging matter more than a connected research knowledge base.
What Do Strella’s Ratings, Customers and Traction Show?
Ratings. As of September 26, 2026, Strella holds 4.5/5 on G2 from 18 reviews, and its Capterra listing has no user reviews, says to contact the vendor for pricing, and lists no free trial. Eighteen reviews is a thin base, so weight a reference call with a current customer above the score.
Customers. In its Series A release, Strella names Amazon, Duolingo, Apollo GraphQL, and Chobani as customers, a mix of consumer brands and software companies that matches its voice-first, stakeholder-reel positioning.
Traction. Bessemer’s April 2026 case study reports $1.6M ARR in Strella’s first year of monetization and over 150% net dollar retention on its first renewal cohort in early 2026. Read that as evidence that early customers expanded their use at renewal; it is the latest public figure, and Strella has not published a newer one.
Participant experience. Strella’s homepage shows a “100% Researcher + Participant NPS” figure without a stated methodology, and its blog reports small samples, such as 13 participants averaging 9/10 likelihood to recommend in December 2024. Ask for the method behind any satisfaction figure before using it in a vendor comparison.
Release pace. Strella shipped a feature most months of 2026: AI-guided setup, 46 languages, Strict and Adaptive modes, participant anonymization, the MCP AI Connector, MNPI checks, audit logs, pass/fail task grading, card sorts and automatic response coding. For a buyer, that pace is a strength; confirm in the demo which of these sit inside your plan tier.
How does User Intuition compare with Strella on each dimension?
In one line: User Intuition puts a senior researcher’s depth behind survey-scale fieldwork, run on the team’s own methodology and backed by evidence it can trace to the verbatim.
How User Intuition differs from Strella
Three differences carry most of the decision, and each is checkable on public pages:
- Laddering by default. Each User Intuition interview runs 20–30 minutes and ladders 5–7 levels by default, and you decide how far the moderator probes; Strella’s moderator follows up to the project-wide depth the researcher configures, and Strella publishes no level count.
- Owned, vetted respondents. User Intuition’s 4M+ vetted panel across 58 countries is its own: our team reviews a video identity interview with every prospective panelist before accepting them, panelists are tracked across studies, and every voice interview is screened for AI-generated or coached answers. Strella recruits through partner panels it names as Respondent and User Interviews, marketed at up to 8M participants.
- Per-project pricing with quality billing. User Intuition publishes $30 per quality voice interview with no subscription and does not bill interviews that fail length, depth and coverage checks. Strella publishes no prices and sells quote-based annual plans.
Both lock question wording (Strella’s Strict mode, User Intuition’s pinned verbatim questions), and both expose research to AI assistants over MCP.
Where the review lands for research teams and agencies
Beyond those three, two checks remain. On methodology control, User Intuition adds study rules, parallel monadic and sequential monadic cells, screeners and hard quotas around the pinned questions. On modality, Strella runs voice with optional webcam in 46+ languages; User Intuition runs voice, video or chat in 80+. Agencies add a delivery check: isolated per-client workspaces, confidential unreleased stimulus and no AI model training on their data. The agency research page covers the project workflow. In-house teams can check the outcome side: Turning Point Brands used User Intuition to identify merchandising as the primary growth lever for its fastest-growing brand, then beat the quarter by over 40% (Turning Point Brands case study).
Speed
User Intuition offers five-minute self-serve setup. Panel studies return 200+ interviews in 24 hours; with your own participants, interviews run in parallel as they respond, with no platform-imposed hourly cap.
There is no demo, quote, or procurement contract to wait on. Any researcher or project lead launches a study the day the brief arrives, while the research lead keeps the method and the readout. Where Strella’s real-time synthesis runs inside an annual plan, User Intuition optimizes for total elapsed time from question forming in someone’s head to answer landing on their screen.
Cost
Where Strella publishes no price and quotes annual plans it describes as usage-based (buyers report roughly $10K-25K+ per study), User Intuition Starter is $30 per quality voice interview ($60 video, $15 chat) with no annual base and no per-seat fee. A five-interview study is $150 with your own participants — AI moderation, analysis, transcripts, and synthesis included — or $300 with recruitment from the 4M+ vetted panel across 58 countries. The Starter plan has no monthly fee, with three free voice interviews with your own participants on signup and no credit card required; per-credit pricing applies once the free three are spent.
For a reviewer sizing a pilot, incentives for your own participants and specialist recruiting quotes are extra, and any interview short on length, depth or coverage is left off the bill. Five such projects cost $750 in platform fees with your own participants. Compare that usage with the current Strella annual plan, recruitment credits, and any Advisory services. Buyer-reported (2026) project quotes remain context for a different scope, not a fixed yearly schedule.
Depth
Where Strella’s voice-to-voice AI moderator runs the discussion guide at a follow-up depth the researcher sets, User Intuition’s moderator is built to adapt inside each conversation. It probes when answers are shallow, redirects when participants stall, recovers threads when conversations drift off-topic, and ladders systematically from concrete behavior through functional benefit and emotional driver to the underlying reason for a choice — 5-7 levels in a single session. This is the same depth-building structure trained human interviewers use in moderated qualitative research, transposed to a moderator that runs interviews concurrently without a platform-imposed hourly cap instead of one trained interviewer working through them serially.
The practical difference is how the researcher achieves depth. Strella exposes detailed moderation settings; User Intuition uses adaptive laddering by default. In a shipping example, follow-ups can connect a delayed order to the participant’s work, the consequences for their team and the reassurance they needed. That helps a researcher decide whether the recommendation should address delivery performance, communication or trust. The explanation comes from the participant’s account, and evidence review helps assess its support across the study.
Scale
Where Strella sits in the panel-reachable lane, recruiting through partner panels marketed as access to up to 8M participants across 46+ languages, User Intuition runs a first-party 4M+ vetted panel across 58 countries, with interviews in 80+ languages. Data quality is enforced at three levels: a person vets every panelist by hand before acceptance, and panelists are tracked across studies; every voice interview is screened for AI-generated or coached answers, with video sessions confirming a real, identifiable person is on screen and engaged; and 5–7 levels of laddered follow-up are hard to fake, with billing only for interviews that pass length, depth and coverage checks. Customer recruitment via CRM integration lets teams field studies against their own customers without sourcing from the panel at all. Where neither platform fields — named-account targeting of specific executives by name, rare clinical populations under 1 in 10,000 prevalence, recruits that depend on warm introductions — a specialist recruiter or managed recruitment service is the fit for both.
The frequency-scaling math differs from Strella’s: where Strella’s cost follows a quoted annual plan plus recruitment credits, User Intuition’s per-study cost stays flat and there is no annual base, quote, or procurement gate sitting between study N and study N+1. Neither platform charges per seat; on User Intuition, added users launch studies directly. Both platforms offer MCP access; User Intuition’s MCP access from Claude, ChatGPT and other MCP clients lets the team query customer insights from inside the AI tools they already work in. The architecture is built for high-frequency research run per project or per client.
Insights
Where Strella pairs per-study outputs — themes backed by verbatims, auto-generated highlight reels, and transcripts — with a research repository its AI Chat can search, User Intuition runs every interview through the Customer Intelligence Hub: an ontology-indexed knowledge graph of themes, codes, sentiment, and verbatim quotes that stays queryable in plain language across every study ever run in the account. Ask “what did enterprise buyers say about pricing in Q1 versus Q2” and the answer comes back grounded in specific quotes from specific participants, drawn from the corpus rather than re-fielded as a new study.
Both platforms let you query past studies; test both on the same cross-study question.
On insight quality, the comparison point to Strella’s verbatim-backed reports is User Intuition’s evidence review. Per learning goal, it shows how well the interviews support each conclusion, flags missing experiences and competing accounts using information power and meaning saturation, and recommends deeper analysis or a targeted follow-up.
Both platforms speak MCP. Strella’s AI Connector creates studies and queries past research; User Intuition’s API and MCP workflows also return recruitment estimates, launch within approved budgets, and deliver findings linked to their sources.
Side-by-side at a glance
| Dimension | Strella | User Intuition |
|---|---|---|
| Speed | Analysis as interviews complete; new buyers start with a demo and quote (no published timeline) | 5-minute self-serve setup; 200+ panel interviews in 24 hours; no sales cycle |
| Cost | No published price; quote-based annual plans (usage-based, no per-seat charges) + prepaid recruitment credits; buyers report roughly $10K-25K+ per study | $150 per five-interview study; $30 per voice interview; no annual base; per-study pricing |
| Depth | Voice-to-voice AI moderation with dynamic follow-ups at a researcher-set default depth; Strict or Adaptive wording | Adaptive moderation that probes, recovers stalls, redirects drift; 5-7 level laddering |
| Scale (audience) | Partner panels marketed at up to 8M participants + expert networks + BYO; 46+ languages | 4M+ vetted panel across 58 countries; 80+ interview languages; panel-reachable + customer-via-CRM |
| Scale (frequency) | Annual plan scaled to research usage; rates not published; annual cost depends on contracted usage | Per-study linear; no annual base to amortize; scales cleanly to 50+ studies/year |
| Scale (team) | One annual plan bought through a demo; no per-seat charges | Self-serve per project; any team member launches independently |
| Insights (quality) | Themes backed by verbatims + auto-generated highlight reels | Themes + verbatim quotes, each finding linked to its recording; evidence assessment per learning goal; cross-study Hub search |
| Insights (persistence) | Research repository searchable with AI Chat and an MCP connector | Customer Intelligence Hub — ontology-indexed, plain-language queries across all past studies |
| Public ratings | 4.5/5 on G2 (18 reviews); 0 Capterra reviews (September 26, 2026) | 4.9/5 on G2 (5 reviews) and 5.0 on Capterra (3 reviews); 98% participant satisfaction across 30,000+ interviews. Counts this small should carry little weight on either side |
| Free trial | None published; demo required, no public sign-up | Three free voice interviews with your own participants on signup, no credit card |
How Do Strella and User Intuition Compare on Security and Compliance Posture?
Strella states SOC 2 and GDPR adherence, and its Vanta trust center lists SOC 2, HIPAA and GDPR as continuously monitored frameworks; it does not publicly state a SOC 2 type. It added participant anonymization in March 2026, automatic MNPI checks for regulated industries in May, and audit logs in June. User Intuition is GDPR & CCPA compliant and SOC 2 Type II compliant; it never trains AI models on customer data, and each client or team works in an isolated workspace with unreleased stimulus kept confidential.
Security review should follow the actual study data: participant identifiers, recordings, transcripts, access, retention, subprocessors, and permitted reuse. Use Strella’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.
Is Strella Worth It in 2026?
Strella is worth it for a team that wants real-time voice interviews, usability tooling or human-led sessions from one vendor, wants a research partner, and can size a year of research on an annual plan. It is a weaker fit when every interview needs laddered depth without configuring it, when respondents should come from a first-party panel, or when research is budgeted project by project.
| Use case | Is Strella a fit? | Where User Intuition fits better |
|---|---|---|
| Qualitative research (in-depth interviews) | Yes, at the follow-up depth you configure | When every interview should ladder 5–7 levels by default |
| User research and usability testing | Yes: task analytics, heatmaps, pass/fail grading and card sorts | Moderated walkthroughs where the reason behind a task matters more than task metrics |
| Concept testing | Yes for reaction-level reads at a configured depth | Monadic and sequential monadic cells side by side, with hard quotas per cell |
| Consumer insights programs | Yes for a team on an annual plan | Repeat waves budgeted per project from a published rate, recruited from an owned, vetted panel |
| Commercial due diligence | Yes through Strella Advisory (pitched as 30+ expert interviews in 10 days) | Self-run studies; specialist audiences are recruited to order, and timing follows incidence |
| Multilingual research | Partly: 46+ languages | 80+ interview languages |
How to Choose Between Strella and User Intuition
The choice between Strella and User Intuition is a choice between two research operating models. Three lenses help orient the decision: research question type, research frequency, and operating model.
Research question × audience type:
| Your research question | Best fit |
|---|---|
| Guide-driven reaction research (concept reactions, ad reads, message tests) with highlight reels | Strella — voice interviews at a configured depth, analyzed as they complete |
| Motivational depth (win-loss, churn drivers, brand identity, founder discovery) | User Intuition — 5-7 level laddering reaches motivation |
| Sprint-cycle stakeholder communication (highlight reel as deliverable) | Strella — auto-generated reels purpose-built for this |
| Continuous customer intelligence (queryable knowledge across studies) | User Intuition — Customer Intelligence Hub queries across studies |
| Human-led or hybrid sessions, card sorts, usability task analytics, MNPI-checked regulated research | Strella — formats User Intuition does not offer |
| Named-account / rare clinical / warm-introduction recruits | Neither — route to a specialist recruiter or managed recruitment service |
Research frequency:
| Your cadence | Best fit |
|---|---|
| 1-2 flagship programs per year on an annual plan | Strella — if an annual partner plan fits the budget cycle |
| Quarterly + a few ad-hoc studies (5/year) | User Intuition — $750 for five five-interview studies with your own participants, published before any sales call; compare against the actual Strella annual quote |
| Monthly continuous research (10+/year) | User Intuition — $1,500 for ten five-interview studies; no annual plan to size |
| Always-on practice (20+/year) | User Intuition — $3,000 for twenty five-interview studies; cost follows usage |
| Sprint-by-sprint customer discovery (50+/year) | User Intuition — $7,500 for fifty five-interview studies; any team member launches |
Strella publishes no prices; buyers report roughly $10K-25K+ per study, so compare these figures with an actual Strella quote for your volume.
Operating model:
| Your team’s research practice | Best fit |
|---|---|
| Annual plan bought through procurement, with a research partner | Strella — buying motion matches |
| Insights team or agency running research per project or per client, with stakeholders commissioning studies on the same account | User Intuition — self-serve scales by adding users who launch studies directly |
| Research consumed as periodic deliverables for stakeholder audiences | Strella — polished per-project packages |
| Research consumed as continuous, queryable knowledge across the organization | User Intuition — Customer Intelligence Hub queries across studies |
| Agency delivering fixed-fee projects | User Intuition — published per-project pricing, isolated per-client workspaces, editable presentation |
Two-platform answer. Some organizations want both: User Intuition for continuous, per-project, motivational-depth research; Strella for the flagship programs a team runs on an annual plan with a research partner. Teams that do not need Strella’s distinct formats or Advisory team can usually run on one platform; the three matrices above show which.
For teams that run research project by project and need laddered depth in every interview, User Intuition is the better fit. Pricing is published, the panel is ready, the trial is free, the rating is 4.9/5 on G2 (5 reviews) and 5.0 on Capterra (3 reviews). Run three free voice interviews with your own participants against your live research question and decide from output, not a sales cycle. Strella remains the right call for the specific use cases the three matrices above identify — teams on an annual plan running guide-driven voice research with highlight reels for stakeholders.
Evaluation Questions for Your Strella Demo
Use these questions in the demo before committing to an annual plan. They are organized by the five dimensions above (speed, cost, depth, scale and insights) so you can verify each one against your team’s actual needs.
Speed:
- What’s the calendar from contract signing to first themed insight for a new audience we haven’t recruited before? Separate in-study fielding time from the pre-study buying and setup steps.
Cost:
- What’s the all-in cost for our typical research volume — annual plan, usage tier, recruitment and incentive credits, any Strella Advisory services, storage and compliance fees over a 12-month horizon? Get the figure for 1, 5, and 10 studies per year.
- What happens if our research usage runs past the plan’s tier mid-year, and do prepaid credits expire?
Depth:
- How does the AI moderator probe off-script answers? Ask to see anonymized interview transcripts where a participant gave an ambiguous answer, volunteered something unexpected, or stalled mid-thought — and what the moderator did next.
- Can the synthesis layer surface motivational drivers (why customers said what they said), or does it mainly summarize what customers said? Ask for examples on a research question where the right answer is “why,” and note the follow-up depth setting each example used.
Scale:
- What’s the panel quality at scale for our specific screener? Niche B2B roles, hard-to-reach professional segments, and rare consumer profiles often expose pass-through differences. Ask for incidence rates and panel pass quality on a screener that matches our actual research target.
- What’s the multi-language moderation quality in each of our target markets — not just “we support 46+ languages,” but how the AI moderation behaves and how stimulus renders in each one, with anonymized examples in our priority languages.
- How do you handle distributed-team usage where 4-5 people across product, marketing, and CX want to launch independent studies?
Insights:
- What does cross-study querying look like in practice? If we run 10 studies this year, can a team member ask a plain-language question across the full corpus next year without commissioning a new study?
- What’s the export path at non-renewal? Can we take transcripts, theme packages, and any indexed knowledge with us?
Security:
- What’s the current SOC 2 attestation status — Type I, Type II, observation period dates? Can we see the report under NDA?
- Where is customer data stored, what’s the retention default, and do you offer a Business Associate Agreement for HIPAA workflows?
Run these questions in parallel against three free User Intuition interviews. Comparative output is the cheapest way to know which model fits your team.