A persona is a humanized representation of a user segment, audience segment, or customer segment.
The persona is presented in a persona profile. A persona profile is the actual representation of the persona. So, a persona is a conceptualize. The person profile is the physical manifestation of that concept.
The persona profile contains various attributes, insights, and information about the persona. Each of these are an element of the persona profile.
Example of a Persona Profile
Here is an example of a data-driven persona profile created by APG, the automated persona generation system.
What elements does a persona profile typically contain?
In this post, we discuss if these artificially generated pictures are good enough for use in personas profiles for real-world systems and applications, which are highly dependent on images for the personas. One of the key aspects of generating personas using a data-driven approach is to be able to represent the persona profile with a matching picture.
Artificial generation of facial images is increasingly popular, with machine learning achieving photo-realistic results.
Yet, there is a concern that the generated images might not fairly represent all demographic groups. This has implications for persona development when approaching the goal of generating the facial pictures for the persona profiles automatically.
In research led by Joni Salminen, we use a state-of-the-art method to generate 10,000 facial images and observe that the generated images are skewed towards young people, especially white women.
The following is a post from the APG Team’s summer 2020 intern, Jaad Mohammed.
If you have ever wondered how photos or headshots are assigned to a persona profile by the AGP system? Well, you’ve come to the right place.
First, you need to understand where exactly APG collects data and how it processes this data to create the basic structure for a set of base personas.
APG links to and accesses data from online social media platforms (e.g., Facebook, Google Analytics, YouTube) via the Application Program Interface (API) of each analytics platform, given an account holder’s permission 
Via the APIs, APG collects the detailed interactions of users with each of the online content pieces on the corresponding platform. This data is available to only owners of a particular social media channel (e.g., YouTube channel) and is not available to the general public
Data provided by these API’s contain variables of gender, age, and country of the set of users, audience members, or customers, provided at an aggregated group level.
Creating personas from large amounts of online data is useful but difficult with manual methods.
To address this difficulty, we present Automatic Persona Generation (APG), which is an implementation of a methodology for quantitatively generating data-driven personas from online social media data.
APG is functional, and it is deployed with several organizations in multiple industry verticals.
APG employs a scalable web front-end user interface and robust back-end database framework processing tens of millions of user interactions with tens of thousands of online digital products across multiple online platforms, including Facebook, Google Analytics, and YouTube.
APG identifies audience segments that are both distinct and impactful for an organization to create persona profiles. APG enhances numerical social media data with relevant human attributes, such as names, photos, topics, etc. Here, we discuss the architecture development and central system features.
Overall, APG can benefit organizations in distributing content via online platforms or with online content that relates to commercial products. APG is unique in its algorithmic approach to processing social media data for customer insights. APG can be found online at https://persona.qcri.org.
In this research on impact of smile on persona perceptions with Soon-gyo Jung, João Santos, and Jim Jansen, we find that persona profiles with a smiling photo result in an increase in perceived similarity with, likability of, and willingness to use a persona.
However, a smile does not increase the credibility of a persona. Our research has implications for the design of persona profiles and adds to previous findings of persona research that the picture choice influences individuals’ persona perceptions in profound ways.