Skimle enables faster analysis of interview transcripts and other qualitative data without sacrificing rigour.
Upload text or audio in any format and have our platform identify common themes and sub-themes across the documents with full two-way transparency. You can explore the data and export ready Word, PowerPoint or Excel reports of the themes. Perfect for researchers, consultants, market researchers, UX teams, policy analysts, lawyers and other knowledge professionals.
Whether you're a consultant analyzing expert interviews, a policy analyst reviewing public consultations, an academic researcher conducting thematic analysis, a market researcher synthesizing customer feedback, or a lawyer reviewing case documents you face the same fundamental challenge:
How do I systematically extract insights from large amounts of text data without spending weeks on manual analysis or settling for superficial AI summaries?
If you've ever worked in consulting, you know the drill: you've just finished 40 expert network calls (via GLG, AlphaSights, InexOne or the likes). The transcripts are sitting in a folder. Your synthesis deck is due Monday. You're staring at 600 pages of interview notes thinking "how do I extract signal from all this noise?"
Or maybe you're knee-deep in due diligence with 1,000+ documents in the data room and 2 weeks to find every red flag. You can't read everything, so you sample and risk missing the critical issue buried on page 67 of document 42.
Picture this: you've just wrapped 60 customer interviews for a B2B brand perception study. The transcripts total 800 pages. Your client wants the presentation by Monday. It's currently Thursday afternoon.
Or maybe you're staring at 5,000 NPS open-ended comments from the quarterly customer satisfaction survey. Your client doesn't want a word cloud showing "pricing" mentioned 147 times. They want to understand *why* pricing is an issue, *which* customer segments care most, and *what specifically* they're comparing to competitors.
