Confusion and Information Triggered by Photos in Persona Profiles

For one of our research projects we investigate whether additional photos beyond a single headshot makes a persona profile more informative without confusing the end user.

We conduct an eye-tracking experiment and qualitative interviews with digital content creators after varying the persona in photos via a single headshot, a headshot, and photo of the persona in different contexts, and a headshot with photos of different people with key persona attributes the gender and age.

Findings show that contextual photos provide significantly more persona information to end users; however, showing photos of multiple people engenders confusion and lowers informativeness. Also, as anticipated, viewing additional photos requires more co.gnitive focus, which is measured by eye-tracking metrics; these metrics are correlated with levels of informativeness and confusion.

Furthermore, various interpretations of the persona based on the choice of photos are biased by the end users’ experiences and preconceptions.

Concerning persona design, findings indicate that persona creators need to consider the intended persona use objectives when selecting photos and when producing persona profiles. Using contextual photos can improve informativeness, but this demands more cognitive focus from end users.

Thus, adding contextual photos increases the perceived informativeness of the persona profile without being obfuscating, but multiple photos of different people do evoke confusion about the targeted persona.

Salminen, J., Jung, S.G., An, J., Kwak, H. Nielsen, L., and Jansen, B. J. (2019) Confusion and Information Triggered by Photos in Persona Profiles. International Journal of Human-Computer Studies. 129(2019), 1-14

Design Issues in Automatically Generated Persona Profiles: A Qualitative Analysis from 38 Think-Aloud Transcripts

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.

Salminen, J., Sengun, S., Jung, S.G., and Jansen, B. J. (2019) Design Issues in Automatically Generated Persona Profiles: A Qualitative Analysis from 38 Think-Aloud Transcripts. The ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR2019). Glasgow, UK. 10-14 March.

Common Questions About Personas (We’ve Got the Answers!)

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In this blog post, we’ve gathered some commonly asked questions about personas. Got more questions about personas? Just send us a message and we’ll address your question!

Frequently Asked Persona Questions:

Continue reading “Common Questions About Personas (We’ve Got the Answers!)”

What is a data-driven persona?

A data-driven persona is derived from verifiable facts about the represented segment of the target population in sufficient amount for quantitative analysis.

An ideal persona is a proxy for a person. The person is the targeted user group, audience, or customer segment. An ideal persona is both describes a segment and predicts the segment behavior.

Data-driven personas come the closest to the ideal persona.

What is a persona profile?

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.).

Below is an example of a persona profile.

a persona profile
This is one example of a persona profile

How to create a persona?

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.

9 Benefits of Data-Driven Personas

Introduction to Data-Driven Personas

Automatic Persona Generation (APG) is a system developed by the persona research team at Qatar Computing Research Institute. APG is defined both as a methodology and a system for automatic creation of personas from online analytics data.

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”