Skimle for customer, UX & market researchers
Every respondent heard. Every insight traceable. Every deadline met.
Whether you run an in-house customer or UX research function, or deliver insights for clients at a market research agency, the core challenge is the same: qualitative data is the richest signal you have, but the volume is too large to analyse carefully by hand. In-house teams face pressure to move at the pace of product decisions. Agencies face clients who want deeper insights on shorter timelines at lower cost.
Skimle handles the mechanical coding that consumes 80% of analyst time. You focus on the strategic interpretation, the “so what”, and the decisions it should drive. What used to take two weeks of coding takes two days with Skimle — without losing the nuance that makes qualitative research worth acting on.
Professional-grade analysis that scales with your research volume
Whether you are analysing 60 customer interviews, 8 focus groups across four markets, or 5,000 NPS open-ends, the challenge is the same: the volume is too large for careful manual reading, but surface-level tools lose the nuance that stakeholders and clients actually care about. Skimle handles scale without sacrificing depth — for both in-house teams and agency researchers.
- Handles interviews, focus group transcripts, open-ended surveys, reviews, and support tickets
- Automated theme identification with every insight linked to verbatim customer quotes
- Segment analysis built in — compare across demographics, product tiers, geographies, NPS bands
- 100+ languages supported — global studies in one project without translation
- Presentation-ready exports in Word, PowerPoint, and Excel in minutes, not days
- Full traceability — show stakeholders and clients exactly where every insight comes from
FROM RAW CONVERSATIONS TO DEFENSIBLE FINDINGS
Analyse focus groups and customer interviews at scale
Focus group transcripts are among the hardest qualitative data to analyse well. Crosstalk, dominant voices, and manufactured consensus can easily mislead — a single vocal participant looks identical to four independent voices unless you track the evidence carefully. Individual depth interviews bring their own challenge: with 20, 40, or 60 transcripts, reading carefully and coding consistently becomes the bottleneck. Skimle builds a systematic theme structure across all your sessions — showing what is consistent, what varies by segment, and what is one participant's outlier view — so your findings are defensible whether you are presenting to a client or an internal stakeholder.
How it works
- 1. Import each group as a separate document
Upload focus group transcripts from Zoom, Teams, Otter, or Fireflies directly, or import corrected transcripts as text or Word files. Each session becomes one document.
- 2. Run analysis across all groups
Skimle reads every transcript and builds themes from the content across all sessions. It does not start from a codebook — it discovers what was actually discussed.
- 3. See what was consistent and what varied
Each theme shows which groups contributed to it and how many times it was raised. Spot what is universal across groups and what was specific to one session or market.
- 4. Assess the evidence distribution
Click any theme to read the supporting quotes and see which group sessions they came from. Evaluate dominant voice effects directly rather than relying on memory.
- 5. Export for the client
Generate the synthesis document with representative quotes by group — ready for the presentation or the full research report.
500 OPEN ENDS. STRUCTURED BEFORE LUNCH.
Gather and analyse open-ended survey responses at scale
Open-ended survey questions produce the richest data in any customer study — and the most time-consuming to analyse. Thousands of responses cannot be read manually, so most teams skim a sample and hope the pattern holds, losing the minority views that often hold the most valuable signals. Skimle reads every response and gives you a structured theme hierarchy with frequency, segment breakdown, and verbatims — from the full dataset, not a sample.
How it works
- 1. Upload the survey export
Import open-ended responses as a CSV file from SurveyMonkey, Typeform, Qualtrics, or any other survey platform. Include respondent metadata columns for segmentation.
- 2. Describe the analytical focus
Frame the analysis around your research question — what are you trying to understand about customers, products, or experiences? Skimle structures themes around your question.
- 3. Review the full theme structure
Skimle builds a hierarchy of themes across all responses — not just the most common ones. Minority viewpoints and outlier signals remain visible.
- 4. Segment the findings
Filter by respondent characteristics — NPS band, product tier, geography, demographics — to understand which themes matter most to which customer groups.
- 5. Export client-ready output
Generate a themed analysis report with verbatim quotes and cross-tabulations — in minutes rather than days.
FROM A FOLDER OF REPORTS TO A STRUCTURED INTELLIGENCE PICTURE
Distil competitor and desk research
Any serious research project involves secondary material alongside primary data — competitor sites, analyst reports, regulatory filings, news archives. Synthesising it all manually means either spending days reading or defaulting to the handful of sources that come to mind easily. Skimle reads every document, surfaces recurring themes, maps contradictions between sources, and links every finding back to its original passage — turning a folder of PDFs into an analysed intelligence picture.
How it works
- 1. Gather and upload your sources
Upload PDFs, Word files, and web content exports — analyst reports, competitor materials, regulatory documents, news archives. Mix them freely with interview data in the same project.
- 2. Define what you are looking for
Frame the synthesis around your client's strategic questions — market dynamics, competitive positioning, regulatory landscape. Skimle organises findings around your framework.
- 3. Surface patterns across sources
Skimle builds a theme structure across all documents — identifying where sources agree, where they contradict, and what the weight of evidence supports.
- 4. Cross-reference with primary data
When desk research and interview data sit in the same project, you can see where secondary sources validate primary findings — and where they diverge. Contradictions are analytically productive.
- 5. Deliver an integrated synthesis
Export a structured report that integrates desk research and primary findings with full source references — defensible and client-ready.
FAQ
Frequently asked questions
- How does Skimle help us compete with low-cost alternatives?
- Low-cost providers compete on price by doing surface-level analysis — word clouds, basic theme lists. Skimle lets you deliver deep, strategic insights at speed, differentiating on value rather than rate card. You maintain premium positioning while improving margins through efficiency. The quality of the "so what" is where professional research firms win, and Skimle frees your analysts to focus on exactly that.
- What if clients question AI-assisted analysis?
- Frame it as AI-assisted human analysis: the AI handles mechanical categorisation, you provide strategic interpretation and recommendations. Skimle's full traceability means you can show clients exactly where every insight comes from — a stronger position than traditional manual synthesis where the coding logic is invisible. Most clients care about insight quality and speed, not your internal tools.
- Can we use this for multi-language global studies?
- Yes. Skimle works in 100+ languages and analyses them natively, without requiring translation first. Upload responses in English, Spanish, Mandarin, German, and Arabic in the same project, and Skimle builds a unified theme structure across all of them while preserving original-language quotes. Global studies no longer require a translation step before analysis.
- How many interviews or responses can Skimle handle?
- Skimle supports up to 1,000 documents per project. For market research, that covers small qualitative studies of 20 to 50 interviews, medium-scale research of 50 to 200 interviews, and large global studies of 200 to 1,000 interviews or survey responses. If you regularly run studies at the upper end, contact us to discuss volume arrangements.
- Is client data secure and confidential?
- Yes. All data is stored on EU-based servers in compliance with GDPR. Your documents are never used to train AI models. Skimle provides Data Processing Agreements for research firms that need them, and we support NDAs for client data. Single-tenant deployments are available for organisations with stricter data sovereignty requirements.
- Can multiple researchers collaborate on a project?
- Yes. Teams can work on the same project simultaneously, with individual annotations and edits preserved. This is useful for peer review, quality control checks, and distributing large projects across junior and senior researchers. One senior researcher can steer the analysis while juniors handle upload and initial review.
About Skimle
Built for professionals, by professionals
Skimle is based in Finland and developed by people who have spent careers doing qualitative analysis under real professional pressure. We built Skimle because we needed it ourselves — and because the existing tools were either too slow, too shallow, or too opaque to defend to a client.
We are trusted by research firms, agencies, Finnish government ministries, over 30 universities, and large companies. All data is stored within the EU and processed according to our strict GDPR policy and terms of service.
For research firms interested in white-label arrangements, enterprise licensing, volume pricing, or reseller agreements, get in touch. We are happy to discuss firm-wide arrangements and custom deployments.