In this research, we examine uses in automatically generating personas from online data using qualitative methods.
The increased access to data and computational techniques enable innovations in the space of automated customer analytics, for example, automatic persona generation.
Automatic persona generation is the process of creating data-driven representations from user or customer statistics. Even though automatic persona generation is technically possible and provides advantages compared to manual persona creation regarding the speed and freshness of the personas, it is not clear (a) what information to include in the persona profiles and (b) how to display that information.
To query these aspects relating to the information design of personas, we conducted a user study with 38 participants. In the findings, we report several challenges relating to the design of automatically generated persona profiles, including usability issues, perceptual issues, and issues relating to information content.
Our research has implications for the information design of data-driven personas.
A persona profile is the end product of the persona creation process. A common layout of a persona profile that is usually 1 page containing a textual description and typically one photo. The textual description will include, along with humanizing elements such as name, demographic information (e.g., education, job, age, etc.) and behavioral information (e.g., interests, goals, purchases, etc.).
Creating a persona involves five steps, which are:
Step 1 Identify: Categorize the population of customers, users, or audience members
Step 2 Collect: Gather data about the Identified populations specifically concerning behaviors (or goals, pain points, etc.) and demographics.
Step 3 Segment: Group the population into unique segments based on unique behaviors, goals, pain points, etc.
Step 4 Generate: Produce identifiable complete segments with combined behavioral and demographic data
Step 5 Enrich: Augment each complete segment with individual characteristics, such as photo, name, etc. to create a complete persona profile for each segment. The set of persona profiles that represents the population is the end product of the process.
Automatic Persona Generation has specifically been developed to address the limitations of manual persona creation. This blog post details the main benefits of data-driven personas compared to manually created personas. Continue reading “9 Benefits of Data-Driven Personas”