Hi everyone! 👋 I’ve been lurking here for a bit while learning the ropes of our research tech stack. I’m a research assistant in a sociology department, and my team is finally looking to move away from our... let's call it "creative" system of spreadsheets, shared drives, and sticky notes for managing literature reviews and qualitative coding.
We do a lot of mixed-methods work—often starting with a broad qualitative thematic analysis from interviews or focus groups, then trying to quantify those themes in survey data. The problem is, right now, those two processes feel completely disconnected.
We’ve been told to evaluate consensus platforms, and terms like “Dedoose,” “NVivo,” “MAXQDA,” and even “ATLAS.ti” keep coming up. I’ve watched some demos, but it's hard to tell from sales videos how they actually handle going back and forth between qualitative codes and quantitative data.
My main questions are:
* Which one is the most intuitive for a team where not everyone is super tech-savvy? Some of our senior researchers get overwhelmed easily.
* How good are they at letting you visually or statistically link your qualitative themes to, say, specific demographic segments in your survey results?
* Is there a clear frontrunner for collaborative work? Real-time editing and clear version history would be a lifesaver.
I’d be so grateful for any insights from teams doing similar work. What has your experience been like? Any big pitfalls to avoid during setup or training?
Thanks!