Personas are a technique for enhanced understanding of users and customers to improve the user-centered design of systems and products. Their creation can be categorized using three persona creation methodologies: Qualitative, Quantitative, and Mixed Methods.
In this post, we describe the Qualitative method and discuss the strengths and weaknesses of this methodology for persona development.
Qualitative persona creation (QUAL) consists of data collection and analysis that are usually manual. Examples of qualitative data collection methods are focus groups, user interviews, and (sometimes) surveys, although surveys can also be a method for quantitative data collection. The user data is often descriptive and unstructured, e.g., texts and interviews. Demographic data can be helpful for use cases such as look-alike analysis. Qualitative analysis approaches typically employed are interpretative, such as open and axial coding. Although one can create assumption-based personas without any data, personas are more commonly produced based on at least some user data or data pooled with fictitious attributes. When actual user data is employed, personas are classically generated using ethnographic means and/or interviews with users), which typically means that the personas rely on sample sizes that may not enable applying statistical analysis.
The point of origin for personas is for software design and software development, and the advocacy for personas was initially two-fold: firstly, (a) to conjure empathy for the target user segments one designs for, and secondly, (b) design teams incorporated the persona technique to understand user interests, needs, desires, pain-points, satisfactions, work processes, etc. For the first purpose, the qualitative persona method has, from the start, been a method that intended to answer the inquiries of why people behave and reason as they do. Qualitative methods were naturally beneficial, and inquiry methods such as ethnography provided instruments, such as contextual inquiry, interviews, and observations that support the formation of an in-depth understanding of users. Accessing in-depth insights for design areas is challenging using quantitative methods, while qualitative methods struggle with analyzing data at scale.
More specifically, the QUAL persona methodology has several strengths explaining why many persona designers prefer and like this approach. The strengths (itemized in alphabetical order) are:
- COMPLEXITY: Examining nuanced and multi-layered user behaviors (i.e., multifaceted user attributes).
- DEPTH: Concentrating on a limited number of persona use cases in substantial depth.
- DESCRIPTIVE: Inductively generating a descriptive model of a user type that uses human judgment and interpretation.
- EMOTIONS: Transmitting the users’ understandings, emotions, views, and beliefs as social constructs into the persona profile.
- EMPATHY: Accessing the causal context of behaviors, needs, goals, feelings, and pain points to produce explanations as to why the persona thinks/does/acts in a certain way.
- EVALUATION: Examining dissimilar user types and circumstances based on manual contrasting of central user attributes.
- EXPERIENCES: Offering an understanding of users’ experiences from a personal level, leveraging the creators’ innate personal perceptions.
- PERSONALIZE: Providing manually curated anecdotes and insights to be employed within the persona profiles.
- SPECIFICITY: Producing rich depictions of explicit user circumstances across scenarios that matter for design.
In contrast, the weaknesses of QUAL are:
- BIAS: QUAL persona profiles can be beset with human biases, stereotypes, and idiosyncrasies.
- EFFORT: Manually creating persona profiles can be time-consuming and costly.
- INVALID: Qualitative personas risk having low credibility levels among persona users who prefer “hard evidence”.
- NARROW: There may be a lack of generalizability of the created personas to other users or contexts.
- REPRESENTATIVENESS: Small sample sizes may result in small user segments possibly being overrepresented and the personas not representative of the entire user population.
For more about persona creation, read:
Jansen, B. J., Jung, S. G., Nielsen, L., Guan, K., & Salminen, J. (2022). Strengths and Weaknesses of Three Common Approaches for the Creation of Personas: Strategies and Opportunities for Practical Employment. Pacific Asia Journal of the Association for Information Systems. 4(3), Article 1.