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About NVivo

Where quantitative data consists of numbers (or text responses, such as categories, that have been converted into numbers), qualitative data typically consists of texts, images, or film footage. Qualitative data obviously requires a different method of analysis than quantitative data. NVivo is a popular software program used to assist a variety of qualitative data forms and analysis approaches. It is designed to help you organize, analyze and find insights in unstructured, or qualitative data like: interviews, open-ended survey responses, articles, social media and web content.

Accessing and using NVivo

NVivo is accessed via the Virtual Laboratory (vLab). For instructions on how to access the vLab, head to the vLab page here.

Launch NVivo via the vLab

First-time users

The videos below introduce the work area and concepts for Windows (6:11") and Mac (5:45") users.


How you use NVivo really depends on the qualitative method and type of data you intend to use. Text-based data (e.g. interview, focus group, or case study transcripts, open-ended survey responses, internet forum discussion threads) and thematic analysis or content analysis methods are most common in qualitative or mixed-methods research projects.

NVivo is invaluable when managing and ‘coding’ conversational transcripts (such as interviews, focus groups, or forum discussions) for thematic analysis. In NVivo, your data files are imported as your ‘Sources’ (e.g. 10 interview transcripts in Word document or PDF form). Themes and subthemes don’t just ‘appear’ after having viewed your data once or twice, regardless of whether you use NVivo, pen and paper, or some other format; you’ll need to generate and refine working ‘codes’ (meaningful commonalities in your data relevant to your research question). These codes can be represented by things called ‘Nodes’ in NVivo, which can then be ordered in hierarchies (to represent themes and subthemes).

Codes can be generated ‘inductively’ or ‘deductively’, and ultimately this approach determines whether your overall approach to the thematic analysis or content analysis is ‘inductive’ or ‘deductive’. An inductive approach to thematic analysis means that you aim to ‘explore’ your data without expectations of what you will find. Codes are generated and refined in a reiterative process, and emerging themes are synthesised in a creative and interpretive way. A deductive approach to thematic analysis means that you aim to ‘confirm’ whether your data is representative of past research findings (either qualitative or quantitative); with this approach, the researcher begins with a particular theory or set of past empirical findings they want to confirm, and develop a coding framework prior to beginning the data coding. The data is coded to fit the predetermined framework, and any data that doesn’t ‘confirm’ the predetermined codes can be subsequently coded using an inductive approach. In this way, a researcher might find that their qualitative data ‘confirms’ past research, ‘confirms’ past research but also adds new empirical or theoretical insights, or does not ‘confirm’ past theory or research and instead generates novel findings.


  • If your data consists of a large number of written responses to open-ended survey questions (particularly for online research), you might find it more efficient to build or export your data into a Microsoft Excel file, and manage and code your data using Excel spreadsheets. In this situation, the spreadsheet ‘rows’ would contain your response cases, and the spreadsheet ‘columns’ would be your codes, and after reiterative refinement and synthesis, your themes and subthemes. The presence or absence of a code, or theme/subtheme, could be indicated using a symbol, letter, or numeral in the cell per case per theme.
  • NVivo can appear confusing at first because its organisational and command terms will be new to you (e.g. ‘nodes’, ‘sources’, ‘sets’). You cannot expect NVivo to give you ‘output’ in the way SPSS does, and instead should think of it more as a tool to assist your organisation, synthesis, and interpretation of the data – for qualitative research, your brain is the analysis program. There’s a reason many researchers are wary of qualitative research, and that’s because it is labour and energy intensive, and you really do need to think about your data and what it means in a way you may not always do when using SPSS (you click the commands and you get a p value, right?). But qualitative research is rewarding, creative, and provides unique insights into phenomena when done well- and NVivo can help you achieve that, so don’t be scared to use it just because it’s strange and new.


Frequently Asked Questions (FAQs)

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