NVivo is a qualitative data analysis software developed by QSR International to help users organize, analyze, and find insights in unstructured qualitative data like interviews, focus groups, surveys, articles, social media and web content. Some of the key ways it can help analyze feedback from different qualitative sources are:
Organizing the data: The first step in analyzing qualitative feedback is organizing the different data sources in NVivo. Surveys can be imported directly from tools like SurveyMonkey or Google Forms. Interview/focus group transcriptions, notes and audio recordings can also be imported. This allows collating all the feedback in one place to start coding and analyzing.
Attribute coding: Attributes like participant demographics (age, gender etc.), location, question number can be coded against each respondent to facilitate analysis based on these attributes. This helps subgroup and compare feedback based on attributes when analyzing themes.
Open coding: Open or emergent coding involves reading through the data and assigning codes/labels to text, assigning descriptive names to capture meaning and patterns. This allows identifying preliminary themes and topics emerging from feedback directly from words and phrases used.
Coding queries: As more data is open coded, queries can be run to find all responses related to certain themes, keywords, codes etc. This makes it easy to quickly collate feedback linked to particular topics without manually scrolling through everything. Queries are extremely useful for analysis.
Axial coding: This involves grouping open codes together to form higher level categories and hierarchies. Similar codes referring to same/linked topics are grouped under overarching themes. This brings structure and organization to analysis by grouping related topics together at different abstraction levels.
Case coding: Specific cases or respondents that provide particularly insightful perspective can be marked or coded for closer examination. Case nodes help flag meaningful exemplars in the data for deeper contextual understanding during analysis.
Concept mapping: NVivo allows developing visual concept maps that help see interconnections between emergent themes, sub-themes and categories in a graphical non-linear format. These provide a “big picture” conceptual view of relationships between different aspects under examination.
Coding comparison: Coding comparison helps evaluate consistency of coding between different researchers/coders by comparing amount of agreement. This ensures reliability and rigor in analyzing qualitative data by multiple people.
Coded query reports: Detailed reports can be generated based on different types of queries run. These reports allow closer examination of themes, cross-tabulation between codes/attributes, comparison between cases and sources etc. Reports facilitate analysis of segments from different angles.
Modeling and longitudinal analysis: Relationships between codes and themes emerging over time can be modeled using NVivo. Feedback collected at multiple points can be evaluated longitudinally to understand evolution and changes in perspectives.
With NVivo, all sources – transcripts, notes, surveys, images etc. containing qualitative feedback data are stored, coded and linked to an underlying query-able database structure that allows users to leverage the above and many other tools to thoroughly examine emergent patterns, make connections between concepts and generate insights. The software allows methodically organizing unstructured text based data, systematically coding text segments, visualizing relationships and gleaning deep understanding to inform evidence-based decisions. For any organization collecting rich qualitative inputs regularly from stakeholders, NVivo provides a very powerful centralized platform for systematically analyzing suchfeedback.
NVivo is an invaluable tool for analysts and researchers to rigorously analyze and gain valuable intelligence from large volumes of qualitative data sources like surveys, interviews and focus groups. It facilitates a structured, transparent and query-able approach to coding emergent themes, comparing perspectives, relating concepts and ultimately extracting strategic implications and recommendations backed by evidence from verbatim customer/user voices. The software streamlines what would otherwise be an unwieldy manual process, improving efficiency and credibility of insights drawn.