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Upload your data
Transcripts, focus groups, open-ended items, or the codebook you already have.
Interview transcripts.txt or .docx
Focus group transcripts.txt or .docx
Open-ended survey items.csv or .xlsx
Your codebook.csv
Findings · Qualitative analysis
Qualitative analysis that keeps every theme tied to a quote.
Upload interview transcripts, focus groups or open-ended survey items. Usercall drafts codes and themes against your research question, links every one to the participant’s words, and lets you keep the codebook. Built for dissertations, grant studies and IRB-approved research.
Used for qualitative analysis by researchers at
How it works
Upload. Draft. Refine. Export with the quotes attached.
The AI does the first pass. You keep the codebook, the memos and the final call. Nothing gets summarized away.
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The AI drafts the first pass
Codes and themes against your research question, or against your codebook. Every excerpt keeps its speaker and the question that prompted it.
3
You refine and export
Merge, split, rename and remove codes. Flag weak findings. Export theme summaries, quote tables and the codebook for the appendix.
Rigor · Traceable findings
Every theme opens to its quotes. Every claim gets a flag.
Reviewers ask where a theme came from. Usercall answers with the excerpts, the question that prompted them and the participants who said them. Weak or contradicted findings are flagged before they reach your write-up.
Open a real reportEvidence-backed
Excerpts, not paraphrases. Each keeps its question.
Auditable
Every finding gets a flag.
- Strong
- Weak
- Overstated
- Contradicted
Your codebook
Start from yours, or edit the AI’s.
Doesn’t invent certainty
Says “not enough evidence” when it isn’t.
Participant-level
Open anyone’s coded transcript.
For academic research
Built for the methods chapter, not just the findings slide.
Dissertations, grant deliverables and IRB-approved studies need more than a summary. They need a trail from every theme back to the transcript.
Usercall for academic research and evaluationThesis and dissertation
Draft codes in hours, then spend supervision time on interpretation. Every theme cites its quotes.
Grant deliverables and evaluation
Turn interviews and open-ended items into theme summaries and quote tables on the reporting cycle.
IRB and ethics
Anonymize participants before or during analysis. Data is encrypted and never used to train models.
Second-coder check
Compare the AI’s first pass with your own coding to surface bias and themes you missed.
Describing the method
Say what happened: AI-assisted first-pass coding, reviewed and refined by the researcher. Export the codebook and quote tables for the appendix.
Multilingual fieldwork
Code transcripts in 50+ languages and compare themes across participant groups.
Compared with QDA software
Lighter than NVivo. More defensible than a chat window.
NVivo, ATLAS.ti, MAXQDA and Dedoose are built for manual coding from scratch. Usercall drafts the coding, keeps the evidence linked, and leaves the judgment to you.
Compared with NVivo, ATLAS.ti,
MAXQDA and Dedoose
QDA softwareUsercallCompare
First pass
Manual coding from a blank codebook. Weeks before the first theme.
Codes and themes drafted in hours.
From your research question, or from the codebook you bring.
Evidence
Coded segments live inside the project file.
Every theme opens to its quotes.
Excerpts keep their speaker and their question. Export quote tables for the appendix.
Scrutiny
Rigor depends on the coder’s discipline.
Findings flagged strong, weak, overstated or contradicted.
Thin evidence is called thin before it reaches the write-up.
Getting in
Per-seat licences and a steep learning curve.
From $89 a month, in the browser. Free to start.
No sales call. Students and grant-funded researchers, ask about pricing.
Need mixed-methods matrices, geodata or a decade of project files in one place? A full QDA suite is the better fit, and we’ll say so.
Pricing
Plans from $89 a month. No sales call.
Pick a plan by how many interviews and files you run a month. Your first interview or analysis is free.
Students and grant-funded researchers, ask about pricing.
Frequent questions
Frequently asked questions.
Is Usercall a QDA tool like NVivo, MAXQDA, or ATLAS.ti?
Usercall is an AI-native qualitative analysis tool. It helps you code, theme, summarize, inspect, and report on qualitative data faster. It is lighter than traditional QDA software, but built around evidence-linked analysis rather than manual coding from scratch.
How do I know the AI did not hallucinate or overstate findings?
Usercall links findings back to supporting quotes and helps flag weak evidence, overclaims, contradictions, and possible missing evidence. This makes it easier to inspect whether each insight is actually grounded in the source data.
How does Usercall analyze qualitative data without losing nuance?
Usercall extracts themes directly from responses while preserving context and meaning. The workflow is similar to how an expert human researcher might approach qualitative analysis or thematic analysis: reviewing transcripts carefully, maintaining a codebook, factoring in each transcript's larger storyline, and linking themes back to evidence. Every theme is connected to supporting quotes, so you can trace insights back to original participant language instead of relying only on summaries.
Can AI replace manual qualitative coding?
Usercall reduces the need for manual coding by generating initial themes, codes, and structure automatically. Researchers can then review, adjust, and refine the results, combining speed with methodological control.
What types of qualitative data can I analyze?
You can analyze interview transcripts, open-ended survey responses, focus group data, voice-of-customer data, and customer feedback. Usercall works with unstructured text-based qualitative data.
Can I edit the AI-generated codes and themes?
Yes. You can refine, merge, split, rename, or remove codes and themes to match your research lens. You can define custom themes, add an existing codebook, adjust AI-generated codes, and refine the structure as your analysis evolves. You stay in control of how insights are organized and interpreted.
Can Usercall be used for academic research or dissertations?
Yes. Usercall is used by researchers and students to analyze qualitative data for academic projects. It helps speed up coding and theme development while maintaining transparency through linked quotes. It can also serve as a baseline to compare with human-coded themes and identify bias or areas that may have been missed. Learn more about Usercall for academic research and evaluation.
How does Usercall handle research ethics and data privacy?
Data is encrypted in transit and at rest, and users can anonymize participant information before or during analysis. Usercall supports common research requirements, including GDPR and IRB considerations, and gives users control over data access and retention.
How do you analyze open-ended survey responses at scale?
Usercall groups open-ended responses into themes and links each theme to supporting quotes. This lets you quickly see patterns across hundreds of responses while still understanding the reasoning, context, and participant language behind each theme.