Data-Driven Personas for Enhanced User Understanding: Combining Empathy with Rationality for Better Insights to Analytics

Persona is a common human-computer interaction technique for increasing stakeholders’ understanding of audiences, customers, or users. Applied in many domains, such as e-commerce, health, marketing, software development, and system design, personas have remained relatively unchanged for several decades. However, with the increasing popularity of digital user data and data science algorithms, there are new opportunities to progressively shift personas from general representations of user segments to precise interactive tools for decision-making. In this vision, the persona profile functions as an interface to a fully functional analytics system. With this research, we conceptually investigate how data-driven personas can be leveraged as analytics tools for understanding users. We present a conceptual framework consisting of (a) persona benefits, (b) analytics benefits, and (c) decision-making outcomes. We apply this framework for an analysis of digital marketing use cases to demonstrate how data-driven personas can be leveraged in practical situations. We then present a functional overview of an actual data-driven persona system that relies on the concept of data aggregation in which the fundamental question defines the unit of analysis for decision-making. The system provides several functionalities for stakeholders within organizations to address this question

Imaginary People Representing Real Numbers: Generating Personas from Online Social Media Data

We develop a methodology to automate creating imaginary people, referred to as personas, by processing complex behavioral and demographic data of social media audiences. From a popular social media account containing more than 30 million interactions by viewers from 198 countries engaging with more than 4,200 online videos produced by a global media corporation, we demonstrate that our methodology has several novel accomplishments, including: (a) identifying distinct user behavioral segments based on the user content consumption patterns; (b) identifying impactful demographics groupings; and (c) creating rich persona descriptions by automatically adding pertinent attributes, such as names, photos, and personal characteristics. We validate our approach by implementing the methodology into an actual working system; we then evaluate it via quantitative methods by examining the accuracy of predicting content preference of personas, the stability of the personas over time, and the generalizability of the method via applying to two other datasets. Research findings show the approach can develop rich personas representing the behavior and demographics of real audiences using privacy-preserving aggregated online social media data from major online platforms. Results have implications for media companies and other organizations distributing content via online platforms.</p

Customer segmentation using online platforms: isolating behavioral and demographic segments for persona creation via aggregated user data

We propose a novel approach for isolating customer segments using online customer data for products that are distributed via online social media platforms. We use non-negative matrix factorization to first identify behavioral customer segments and then to identify demographic customer segments. We employ a methodology for linking the two segments to present integrated and holistic customer segments, also known as personas. Behavioral segments are generated from customer interactions with online content. Demographic segments are generated using the gender, age, and location of these customers. In addition to evaluating our approach, we demonstrate its practicality via a system leveraging these customer segments to automatically generate personas, which are fictional but accurate representations of each integrated behavioral and demographic segment. Results show that this approach can accurately identify both behavioral and demographical customer segments using actual online customer data from which we can generate personas representing real groups of people

Telling stories with personas

Even though the persona method is a well-known tool in the Human-Technology Interaction field for knowing users and their goals, tasks and environments, there are varying opinions about how personas should be developed and used. Many agree that combining personas with scenarios and user stories is useful, but scenarios and user stories can also be defined and used in various ways. The purpose of my master's thesis is to examine with a literature review different ways to develop and use personas together with scenarios and user stories. My thesis aims to gain a broad picture of the topic rather than confirm one, single perspective. I will search for sources in multiple places since quantitative research alone cannot provide complete enough answers to my research questions. I have divided personas into four types based on my literature review. Manual, semi-automatic and automatic personas are based on mostly user research, but they vary on how many steps in their development are done manually. Expert personas are based on knowledge gathered from stakeholders, literature and other experts. Designers should decide the type of persona based on the purpose of the project and available data and resources. The most important elements in persona description are a photo, name, background information, goals, pain points and story. All personas in the project should be comparable by using the same elements in persona descriptions and same layout in persona documents. Deciding what sources are included in a literature review and how extensively new sources are searched for are always subjective decisions. Another limitation of my thesis is that it does not cover visual design methods, such as storyboards or user journeys. There is some academic research about personas, scenarios and user stories, but knowledge about this topic could be broadened and deepened by conducting more research on the effectiveness, popularity and usage of these methods. Comparisons of practices between countries and companies would also be interesting