Typically, when a product is undergoing its design/redesign stages. The people involved in the designing stage can benefit if they can know what’s in the mind of their targeted customers, such as: Who are they? Where are they from? What are they looking for? What are their goals?
This situation is where personas come in handy!
Since personas are imaginary people that represent the user, audience, or customers of a market segment, stakeholders can quickly make informed decisions catering to the user’s needs and design a more user-centric product.
However, the creation of personas can be a time taking manual process requiring much patience and dedication, from collecting data to use, analyzing the data to identify different behavioral patterns, figuring out what type of information should be presented in a persona profile, and the appropriate template required to display a persona profile.
This is how the APG system comes into the picture, as an automated creation tool for creating personas!
APG – Automated Persona Generation!
The APG system algorithm can automatically create personas to achieve an organization’s requirements in a short time span. We are talking HOURS!
APG can make sets of personas for social media and web analytics platform, which include YouTube, Facebook, Instagram, and Google Analytics. APG also works with in-house customer data.
The complex data from these websites are processed in real-time to create personas and presented to you on the APG website in the form of persona profiles as show below.
The personas represented on APG are data-driven as the system continuously collect data from the platforms, this means that the personas get updated on a timely schedule and therefore become relevant artifacts that can you can refer to at any moment, unlike conventional manual methods of persona creation that can get outdated within days of creation.
Consider APG for your personas!
Jung, S., An, J., Kwak, H., Ahmad, M., Nielsen, L., and Jansen, B. J.(2017) Persona Generation from Aggregated Social Media Data. ACM Conference Extended Abstracts on Human Factors in Computing Systems 2017 (CHI2017). Denver, Colorado. p. 1748-1755. 6-11 May.