Best data analysis software for students (interview with Quirkos developer - Dr Daniel Turner)

Qualitative researchers often get stuck between two worlds: the simplicity of paper/Word/Excel and the power—but cost and complexity—of heavyweight tools like NVivo, Atlas.ti, and MAXQDA. Quirkos is built to bridge that gap with an interface designed for fast, beginner-friendly coding of small, semi-structured datasets such as interviews and focus groups, while still supporting practical needs like attributes and values for comparisons.

Daniel Turner, founder of Quirkos, traces the software’s origins to his own experience doing human geography research—work that blends people and place, and often relies on qualitative methods. After a PhD and multiple postdoctoral roles, he ran into a recurring frustration: qualitative researchers needed software that was intuitive enough to start quickly, yet many existing options were either manual (and painful later) or overly complex and expensive. He also saw a pattern among students: they avoid qualitative software not because they want to, but because they fear the learning curve and don’t want to spend days mastering menus when their real goal is analyzing their data.

Turner describes how Quirkos began as a personal project while he was still in academia, then moved into full-time development after about a year of behind-the-scenes work. A small group of roughly 12 beta testers—drawn from academia and market research—helped validate the approach and accelerate adoption. Although Turner initially lacked programming skills, he leaned on early advice from friends familiar with databases and Python, then hired a freelance developer (Adrian) to turn his specification into working software. That collaboration mattered: the developer produced in about a week what Turner estimated would have taken him months.

A key design choice is Quirkos’s “bubble” visualization for codes. Instead of spreadsheet-like grids and dense menus, codes appear as draggable bubbles that grow as more text is coded into them. This creates a live feedback loop: themes visibly expand as analysis progresses, helping researchers stay engaged with the data rather than getting detached in separate visualization steps. Turner frames qualitative analysis as a flow, and Quirkos aims to keep coding and sense-making evolving together.

Compatibility and portability also address a major pain point in qualitative research workflows: losing access to a collaborator’s software can strand projects. Quirkos supports the “refy qda Exchange format,” a newer standard that enables exporting and importing projects across Quirkos, NVivo, Atlas.ti, and MAXQDA. That reduces the risk of dead-end collaboration and allows researchers to use each tool for what it does best.

Pricing is positioned as student-first. Quirkos offers a one-off student license for £55 (for one computer, transferable if the device changes) and a cloud subscription (Quirkos CL) for £6 per month for students, with project data stored on secure servers and accessible after logging in. A trial is available: the full offline version for four weeks and the cloud version for 14 days, plus video tutorials and support materials.

Beyond software, Turner connects the discussion to career realities after PhD training—highlighting that academia is competitive, post-PhD career support is limited, and many researchers find viable paths outside universities without treating the decision as failure.