We are almost finished with our book,Data-Driven Personas by Bernard J. Jansen, Joni O. Salminen, Soon-Gyo Jung, and Kathleen Guan, Hamad Bin Khalifa University (HBKU) and University College London. Morgan & Claypool Publishers.
Data-Driven Personas, part of Synthesis Lectures on Human-Centered Informatics
Image C: Artificial male picture [A], Real male picture [B], Artificial female picture [C], and Real female picture [D]. Among the male/female personas, all other content in the persona profile was the same except the picture that alternated between Artificial and Real.
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.
After APG creates a base persona for a set of user data by following its unique sequential method comprises of [1]:
Identifying distinct user interaction patterns from the data,
Linking these distinct user interaction patterns to user demographic groups,
Identifying impactful user demographic groups from the data,
Creating base personas via demographic attributes, and
Enriching these base personas to create rich personas description.
The above method is explained in detail when we talk about how the systems finds picture & age of a persona.
Now that we have a base persona, the system queries a Facebook Application Program Interface (API) to collect information like related demographics such as the personas job by feeding the API details of the base personas interests and demographics data.
These are the steps taken by APG to add an job to a Persona Profile.
The following is a post from the APG Team’s summer 2020 intern, Jaad Mohammed.
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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 [1]
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.
Remarkably, with the combining of personas and analytics, the strengths of each approach help offset the deficiencies of the other. Conceptually, personas are easy for people to understand and generate empathy for the user, but personas are perceived as not granular and not actionable. Analytics data can be granular and actionable, but analytics can be cumbersome for employment and difficult for end users to comprehend. Nonetheless, the combination of both leverages the strengths and limits the weakness of each.
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.