Personas are a technique for enhanced understanding of users and customers to improve the user-centered design of systems and products. Their creation can be categorized using three persona creation methodologies: Qualitative, Quantitative, and Mixed Methods. In this post, we describe the Mixed Methods method and discuss the strengths and weaknesses of this methodology for persona …
Mixed Methods Personas: Strengths and Weaknesses Read More »
Personas are a technique for enhanced understanding of users and customers to improve the user-centered design of systems and products. Their creation can be categorized using three persona creation methodologies: Qualitative, Quantitative, and Mixed Methods. In this post, we describe the Quantitative method and discuss the strengths and weaknesses of this methodology for persona development. …
Personas can be a force multiplier in reaching your three categories of non-customers – the Edge Non-customers, the Refuse Non-customers, and Unknown Non-customers. Algorithmically-Generated Personas are great for humanized representation of your existing customers presented in understandable chunks of information. These data-driven personas are great for team communication while creating content and designing systems, along …
Personas for your non-customers – the Edge, the Refuse, and Unknown non-customers Read More »
Algorithmically generated personas can help organizations understand their social media audiences. However, when using algorithms to create personas from social media user data, the resulting personas may contain toxic quotes that negatively affect content creators’ perceptions of the personas. To address this issue, we have implemented toxicity detection in an algorithmic persona generation system capable …
Organizational user-centric design is crucial for developing information technology that offers optimal usability and user experience. Personas are a central user-centered design technique that puts people before technology and helps decision makers understand the needs and wants of the end-user segments of their products, systems, and services. However, it is not clear how ready organizations …
Derived from the notion of algorithmic bias, it is possible that creating user segments such as personas from data results in over- or under-representing certain segments (FAIRNESS), does not properly represent the diversity of the user populations (DIVERSITY), or produces inconsistent results when hyperparameters are changed (CONSISTENCY). Collecting user data on 363M video views from …
TL;DR: A big challenge for data-driven personas is that their users rarely participate in their creation. This evokes the question of how to develop techniques that enable participatory design of data-driven personas. There is a line of thought within persona research that argues something like this: personas are less useful than their creation process. The …
Why Personas Could Be Less Useful than the Process of Creating Them Read More »
