Quantitative Personas: Strengths and Weaknesses

Strengths and Weaknesses of Three Common Approaches for the Creation of Personas: Strategies and Opportunities for Practical Employment
s of Three Common Approaches for the Creation of Personas: Strategies and Opportunities for Practical Employment.

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 Quantitative method and discuss the strengths and weaknesses of this methodology for persona development.

Quantitative persona creation QUANT has been used for some time with quantitative data collection methods, such as surveys and system interaction logs. However, the availability of a large volume of online user data, both from online surveys at scale, internal sources (e.g., CRM systems), and digital analytics services, combined with increasingly sophisticated algorithmic procedures and interactive persona systems, encourage the creation of personas via quantitative data and using statistical methods.

Specifically, collecting user data via APIs has radically increased the viability of quantitative persona creation. Prominent social media services (e.g., Facebook, YouTube) and sizeable online analytics platforms (e.g., Adobe Analytics, Google Analytics) can be used to collect this online data.

Relying on these opportunities of data availability, the QUANT persona methodology has numerous strengths that illuminate why it has increased support and use in many persona development settings. The strengths include:

  • EVALUATION: Permits the testing hypotheses about users developed before creating the personas.
  • PRECISION: Collected data is more concise, precise, and statistically reliable than qualitative observations.
  • PRESENTATION: User findings can be dynamically presented and updated as the data is based on large sample sizes, even up to millions of user interactions.
  • REPEATABILITY: The persona creation can be replicated using the same datasets, arriving at the same conclusions, which adds capacity to simplify user insights about many diverse segments and populations.
  • SIMPLICITY: The capacity to construct a series of data processing and analysis steps eliminates the sporadic nature of manual data analysis and enables more predictable cause-and-effect relationships.
  • SPEED: Quicker data collection and analysis relative to the QUAL approach.
  • TESTING: Persona profiles can be leveraged for quantitative predictions, such as the persona‚Äôs topical interests and preferred online content.
  • VALIDITY: Permits the validation and testing of created theories about users using observational data or experimental designs.
  • VOLUME: Applicability for the studying of large numbers of users.

The QUANT approach has shortcomings, however. These include:

  • COMPLEXITY: Gathered user data may necessitate complex algorithms for analysis that require competencies not always available within a design team.
  • DISCONNECTION: Segmenting may not represent the needs and preferences of the end users, and the designer might feel disconnected from the personas due to a lack of involvement in their creation.
  • OUTLIERS: Statistical influence of the larger user segments in the persona creation process may mask the impact of outliers and marginalized user groups, thereby harming inclusive design goals. SR:
  • TARGETED: Created personas may represent existing users and not the desired/potential users, while also being somewhat limited in what insights can be obtained using statistical analysis.

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.