Signal & Noise
Skimle's resource centre dedicated to high quality analysis using modern methods
Skimle Ask: qual at scale with AI interviews that ask why
How Skimle Ask runs AI interviews at scale: 8 question types, branching, follow-ups and a customer experience example that turns chat replies into numbers.
Discovering themes in the data using metadata variables: a worked example in Skimle
How to add, enrich and group metadata variables in Skimle, then use them to find where segment, score or time explains real differences in what people say.
Interview recording, transcription and analysis: a practical 6-step setup
How to record, transcribe and analyse interviews in 6 steps: phone recording tips, AI transcription, transcript review, and AI-assisted analysis with Skimle.
Transcribing audio and video interviews with Skimle: from recording to traceable quotes
Transcribe interview recordings in Skimle: upload audio or video, get a speaker-labelled transcript in minutes, and play every quote from the moment it was said.
How to use agentic analysis in Skimle: 7 stages from a research question to a written answer
A guide to Skimle's agentic analysis: state a question, objective or deliverable, confirm the framework, and get coded evidence plus a written, cited answer.
How to code qualitative interviews with AI using Skimle: a step-by-step walkthrough
A practical walkthrough: how to code qualitative interviews with AI in Skimle, from adding transcripts to reviewing codes, slicing by metadata, and exporting.
How to find themes across a large set of interviews: a practical guide
Got 40 interview transcripts and need to find the patterns? This step-by-step guide walks through the complete analysis workflow: from transcript preparation to synthesised themes you can actually pre...
Turning interview notes into insights at scale: collaboration, repositories and shared process
How consulting and research teams set up shared Skimle projects where multiple researchers can upload transcripts, code data consistently, and synthesise findings together. Includes a framework for is...
Skimle's Agentic Chat and MCP: how humans and agents can collaborate in qualitative research
Skimle's Agentic Chat lets researchers and AI agents work side by side on structured project data, with full source traceability and human control throughout.
Step-by-step guide to agentic analysis workflows with agentic chat and MCP
A complete walkthrough of using Skimle's Agentic Chat and MCP connections. Work together with smart agents to structure, analyse and visualise qualitative data. A practical approach to step to the fut...
How to do thematic analysis with AI: a practical guide for 2026
A methodologically grounded guide to AI-assisted thematic analysis: where AI accelerates the process, where it can't replace researcher judgement, and how to do it rigorously.
Analysing customer feedback with Skimle: digging deeper into what customers are telling you
Learn how to import customer feedback CSVs into Skimle, set metadata fields, and let AI surface hidden themes by product, time period, and more.
Manual coding and REFI-QDA export - combining Skimle's AI analysis with manual workflows
How to use Skimle's manual editing tools to refine AI-generated codes, and how to export your full coding scheme to NVivo, MAXQDA, or ATLAS.ti via REFI-QDA.
End-to-end workflows - Importing and exporting data with Skimle
We're big believers in building a tool that integrates with the day to day work of knowledge professionals. In this post we explain what is possible with Skimle and what is coming next!
Analysing interviews and other documents in multiple languages with Skimle
You interviewed people in French, German, English and Swedish, and need to analyse also some Finnish text and Spanish emails as well. How to cope with multiple languages?