Discovery interviews
Explore customer problems and decision criteria with adaptive follow-up questions rather than a rigid survey alone.
Independent tool overview
User Evaluation at a glance
User Evaluation is an AI-powered qualitative research platform for planning studies, recruiting real participants, running adaptive interviews and analyzing source-linked evidence.
Visit the official User Evaluation site ↗
- Best for
- Product, UX and customer-insights teams running qualitative research
- Participants
- Bring your own contacts or recruit consumer and B2B panels
- Study formats
- AI interviews, adaptive surveys, fixed surveys and live interviews
- Outputs
- Transcripts, cited insights, clips, reports, decks and CSV exports
- Free plan
- 100 agent credits per month, 3 projects and limited processing
- Paid plans
- Pro from $49/month; Team from $199/month, plus interview bundles
Overview
What User Evaluation is
User Evaluation brings study planning, participant recruitment, AI-moderated interviews and evidence-based analysis into one research workspace. Teams can recruit from the platform's consumer or B2B panels, invite their own participants, or upload existing recordings and documents for analysis.
Its core differentiator is an AI researcher that can draft screeners and interview guides, conduct adaptive audio interviews, follow up on participant answers, and turn transcripts into cited themes, clips, reports and presentation decks. It can reduce the operational work around qualitative research, but the quality of the result still depends on sound study design, informed consent, representative recruiting and human review of the underlying evidence.
Use cases
Who User Evaluation is best for
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Concept and prototype feedback
Collect structured reactions from target participants and preserve the transcript or clip behind each finding.
Continuous customer research
Give a product or insights team a repeatable workflow for recruiting, interviewing, tagging and reporting.
Research repositories
Upload interviews, calls, documents and CSV data, then search and synthesize evidence across a project.
Teams with limited researcher capacity
Automate moderation and first-pass analysis while keeping a human owner responsible for methods and conclusions.
Capabilities
Core User Evaluation features
AI study planning
Turn a research brief into a proposed plan, audience definition, screener, interview script and study settings.
AI-moderated interviews
Conduct audio interviews with real participants, follow a guide and ask adaptive follow-up questions based on responses.
Multiple study formats
Run AI-curated interviews, conversational surveys, fixed-question surveys or scheduled human-led live interviews.
Participant recruiting
Invite an existing contact list or recruit eligible consumer and business participants through the platform's pools.
Live research oversight
Listen during supported sessions, follow captions and receive bounded moderator suggestions without replacing the participant-facing consent process.
Transcription and source search
Process uploaded audio, video, documents and CSV files, then search the indexed material from the project workspace.
Cited AI insights
Ask questions across transcripts and inspect citations that link an answer or proposed insight back to its source.
Tags, clips and notes
Organize recurring themes, save supporting video or audio moments and retain researcher-authored context alongside AI outputs.
Reports and decks
Generate source-linked reports and export presentations, charts, clips and structured data for stakeholders.
Team and enterprise controls
Higher-level workflows include shared workspaces, viewer access, roles, audit history, retention controls, SSO and SCIM options.
Process
How the User Evaluation workflow works
Step 1
Define the decision
Write the research question, intended audience and decision the study needs to inform before generating a guide.
Step 2
Review the study design
Edit the proposed screener and script for neutral language, logical sequencing, accessibility and appropriate handling of sensitive topics.
Step 3
Choose participants
Invite consented contacts or configure consumer or B2B recruitment criteria, incentive and participant cap.
Step 4
Pilot the interview
Run a small test and compare AI moderation with a skilled human on adherence, probing depth, leading questions and participant drop-off.
Step 5
Launch and monitor
Collect interviews or surveys, watch completion quality and replace invalid sessions under the platform's stated policy when applicable.
Step 6
Validate the evidence
Check citations, transcripts and clips before accepting themes, then document sample limits and export the final report or deck.
Cost
User Evaluation pricing and free plan
User Evaluation combines subscriptions with one-time interview credits. Participant incentives are separate, and the official pricing page should be checked before purchase because quotas and bundle rates can change.
Free
$0
A limited workspace for trying the research agent, processing and exports.
- 100 agent credits per month
- 3 projects and 1 GB storage
- 3 audio/video processing hours
- Trial interviews and research exports
Pro
$49/month
For an individual researcher running recurring studies with their own participants.
- 5 own-participant AI interviews per month
- 30 audio/video processing hours
- Unlimited projects and 25 GB storage
- Reports, decks, clips and tags
Team
$199/month
For a research team that needs pooled usage, shared workspaces and viewer access.
- 25 own-participant AI interviews per month
- 100 pooled processing hours
- 5 authors and unlimited viewers
- 1 TB storage
Own-participant bundle
From $90 one time
Non-expiring interview credits when you supply the participants.
- 10 interviews for $90
- 25 interviews for $200
- Participant rewards are separate when applicable
Consumer-panel bundle
From $240 one time
Recruit eligible consumer participants from the platform's pool.
- 10 interviews for $240
- 25 interviews for $550
- Rates are based on valid completed interviews
B2B-panel bundle
From $440 one time
Recruit professionals who match business-role criteria.
- 10 interviews for $440
- 25 interviews for $1,000
- Specialized audiences may require careful feasibility review
Packaged or managed study
From $990
A more service-led option for recruited interviews and a completed research deliverable.
- Packaged study listed at $990 for 10 interviews and a cited report
- Managed study listed from $1,500
- Confirm scope, recruiting criteria, turnaround and deliverables before purchase
Pricing checked . Check current pricing at the source ↗
Assessment
User Evaluation strengths and limitations
Where it stands out
- Connects study planning, recruiting, moderation, analysis and reporting in one workflow
- Uses real participants rather than presenting synthetic personas as customer evidence
- Adaptive follow-up questions can capture context that fixed surveys miss
- Supports both bring-your-own participants and recruited consumer or B2B panels
- Citations make it easier to trace AI-generated findings back to transcripts and files
- Combines interviews, surveys, uploads, clips, tags, reports and decks
- Unlimited viewer access can simplify stakeholder review on listed paid plans
- One-time interview bundles do not expire according to the current pricing page
What to consider
- AI moderation can miss emotional nuance, fail to probe a promising answer or ask a leading follow-up
- Sensitive, high-stakes or emotionally difficult research may require a trained human moderator and an escalation plan
- Qualitative interviews do not become statistically representative simply because they are automated or run at larger volume
- Panel and screener choices can introduce selection bias, professional-participant behavior or weak audience fit
- Researchers remain responsible for informed consent, recording notices, incentive terms and participant withdrawal or deletion requests
- Interview recordings, transcripts, screen context and demographics may contain personal or sensitive information
- The privacy policy says research content may be processed by contracted AI providers, so teams should complete a current security and data-processing review
- User Evaluation says it does not use Customer Data to train models it develops, but third-party AI processing is governed by relevant provider terms and agreements
- AI-generated themes can overgeneralize, flatten disagreement or select persuasive quotes that do not reflect the full sample
- Every important finding should be checked against the cited transcript, clip and contradictory evidence
- Transcription quality can fall with accents, crosstalk, poor audio, jargon or multilingual conversations
- Participant incentives are separate from platform pricing and can materially change total study cost
- Monthly interview allowances, processing hours, author seats and panel credits differ by plan
- Enterprise buyers should confirm current SSO, SCIM, audit, retention, residency and contractual controls directly with the vendor
Compare
User Evaluation alternatives
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Data Analysis
Survicate AI Surveys
Choose Survicate when lightweight multi-channel surveys and automated feedback analysis matter more than AI-moderated interviews.
Explore Survicate AI Surveys →Marketing
SurveyMonkey AI
Choose SurveyMonkey AI for a mature survey workflow, broad question formats and conventional quantitative feedback collection.
Explore SurveyMonkey AI →Business Operations
Fireflies AI
Choose Fireflies when the main need is recording, transcribing and searching calls rather than recruiting and moderating research participants.
Explore Fireflies AI →Project Management
Fathom
Choose Fathom for simpler meeting transcription and summaries when a full qualitative-research platform would be excessive.
Explore Fathom →Questions
User Evaluation FAQs
What is User Evaluation?
User Evaluation is a qualitative-research platform that uses AI to help plan studies, recruit real participants, moderate interviews or surveys, analyze transcripts and produce source-linked reports.
Does User Evaluation use real people or synthetic users?
Its interview workflow is built around real participants. You can invite your own contacts or recruit from consumer and B2B pools; the AI acts as moderator and analyst rather than pretending to be the customer.
How much does User Evaluation cost?
The official pricing page lists a Free plan, Pro at $49 per month and Team at $199 per month, plus one-time own-participant, consumer-panel and B2B interview bundles. Incentives and some services cost extra.
Can it recruit participants?
Yes. You can use platform recruitment pools or bring your own participant list. Carefully review screener criteria, feasibility, participant quality and incentives before launching.
Can AI replace a human user researcher?
No. It can automate study setup, moderation and first-pass analysis, but a qualified human still needs to own methodology, consent, sampling, bias review, sensitive-topic handling and final conclusions.
Are AI-generated insights cited?
The platform says answers and proposed insights can link back to source files. Researchers should still open those citations, read the surrounding transcript and look for contradictory evidence.
What data should teams avoid uploading?
Avoid unnecessary personal, confidential or regulated data. Before using recordings or transcripts, confirm participant notices, legal basis, access controls, retention, deletion and the vendor's current subprocessors and security terms.
How should a team evaluate User Evaluation?
Run a small pilot using a known research question. Compare AI and human moderation on completion, question adherence, probing depth, leading behavior, transcript accuracy, evidence fidelity, participant experience and total cost.
Bottom line
Our User Evaluation verdict
User Evaluation is most compelling for product and insights teams that need to run more real-participant qualitative research without staffing every interview live. Its integrated recruiting, adaptive moderation and source-linked analysis can save substantial coordination time. Treat it as research infrastructure, not an autonomous truth machine: pilot the moderator, protect participant data, inspect every important citation and keep a skilled researcher accountable for the study design and conclusions.
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