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.
To get a comprehensive understanding of this process, we will take you through a gist of how the APG system creates a persona profile whose final goal is to accurately represent the audience segment of a social media platforms (Facebook, Instagram, YouTube or Google Analytics) by analyzing user interactions with the specified account holders content.
For this, APG needs to gather detailed information regarding the interactions of users with each of the online content pieces on the corresponding platform.
The following is a post from the APG Team’s summer 2020 intern, Jaad Mohammed.
If you ever thought how the APG system assigns a name to a data-driven persona, you’ve come to the right place.
Since personas are representations of a typical user segment for a product’s current customer base, the persona needs a name! Nothing could make a persona feel more like a real person than giving it a name.
Below, we walk you through basics of what APG does to create a persona and to assign a name to the persona profile.
First and foremost, we need some kind of statistical data that our persona represents. For this, APG leverages privacy-preserving aggregated data of user interactions with product content posted on major online social media and other analytics platforms, such as Facebook, YouTube, and Google Analytics, etc. .
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.
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.
Using the APG system for automatic persona creation from real data is both a working system and an on-going research project. With APG, we have developed a methodology to automate the creating of imaginary people. These imaginary people are personas. We do this by processing complex behavioral and demographic data of social media audiences.