Data analysis methods are used to analyze the outputs of qualitative research, from interview transcripts, written or oral diaries to visual artefacts or objects. Design research has an additional step of data synthesis to make research data more actionable.
This is the process of labeling and organizing qualitative data to identify different themes and the relationships between them. It often involves the creation of code books, especially when coding is undertaken by several researchers.
Transcript analysis involves undertaking a close reading of an interview transcript to identify key words, themes and patterns. This can focus on categories that have been preset by the researcher (etic) and also on themes that emerge from the interview itself (emic) (see Coding above). When large amounts of transcripts need to be analysed, software such as NVivo is often used. This necessitates establishing codes for analysis first.
This type of analysis is used to examine patterns in communication systematically, by determining the presence of certain words, themes or concepts within a qualitative data set (eg. text, transcript). Researchers can quantify how often an element of the text is used (breath) and also analyze the meaning and relationships of these elements (depth).
This type of analysis involves a systematic examination of written, spoken or other forms of language, to understand how patterns of meaning are socially constructed. It aims to understand how language is used in real-life situations and the rules and contexts that shape its use.
Also known as “SNA”
This type of analysis involves investigating social structures through networs and graphs, distinguishing between nodes and links. It can be used to systematically map the relationships between members of a particular research community.
This type of analysis brings together researchers and stakeholders to interactively process raw data into patterns and themes. It focuses on articulating the most valuable learnings that emerge from research and results in succinctly formulated insights statements.
This type of analysis focuses on understanding the visual artefacts produced during research, including drawing, photos, maps and videos. It aims to systematically elicit the information contained in these creations and relate them to other research outputs.
Personas are fictional characters used especially in design research that represent the different user types that might use a service, product, site, or brand similarly. Personas can be used to build out user profiles with images, brief descriptions, demographics and other relevant information.
This method visually illustrates how users engage with a particular intervention and feel about their engagement. It captures and articulates key insights of a user journey, focusing on their needs, perceptions and processes.
These profiles are created by extracting the goals, motivations, expectations and behaviors of potential users from the research data, in order to better understand how they might engage with a new intervention. This can then lead to segmentation, where potential users are divided into groups that share similar characteristics.