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

In this research, 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.

An, J., Kwak, H., Salminen, J., Jung, S.G., and Jansen, B. J. (2018) Customer segmentation using online platforms: isolating behavioral and demographic segments for persona creation via aggregated user data, Social Network Analysis and Mining. 8(1), 54.

Research Concerning: Are Personas Done? Evaluating their usefulness in the age of digital analytics

In research led by Joni Salminen, we conceptually examine the use of personas in an age of large-scale online analytics data.

Based on the criticism and benefits outlined in prior work and by practitioners working with online data, we formulate the major arguments for and against the use of personas given real-time online analytics data about customers, analyze these arguments, and demonstrate areas for the productive employment of data-driven personas by leveraging online analytics data in their creation.

Our key tenet is that data-driven personas are located between aggregated and individual customer statistics.

At their best, digital data-driven personas capture the coverage of the customer base attributed to aggregated data representations while retaining the interpretability of individual-level analytics; they benefit from powerful computational techniques and novel data sources.

We discuss how digital data-driven personas can draw from technological advancements to remedy the notable concerns voiced by scholars and practitioners, including persona validation, inconsistency problem, and long development times.

Finally, we outline areas of future research of personas in the context of online analytics. We argue that to survive in the rapidly developing online customer analytics industry, personas must evolve by adopting new practices.

Salminen, J., Kwak, H., An, J., Jung, S.G., and Jansen, B. J. (2018) Are personas done? Evaluating their usefulness in the age of digital analytics. Persona Studies. 4, 2, 47-65.

Is More Better?: Research Concerning the Impact of Multiple Photos on Perception of Persona Profiles

Background: We investigate if and how more photos than a single headshot can heighten the level of information provided by persona profiles. We conduct eye-tracking experiments and qualitative interviews with variations in the photos: a single headshot, a headshot and images of the persona in different contexts, and a headshot with pictures of different people representing key persona attributes. We conduct the within-subject experimental study with 29 participants. The participants were selected to reflect the staff working with news content on a daily basis and formed a diverse pool of individuals originating from 19 different countries (e.g., Egypt, Georgia, Germany, Syria, UK, USA, etc.). Continue reading “Is More Better?: Research Concerning the Impact of Multiple Photos on Perception of Persona Profiles”

9 Benefits of Data-Driven Personas

Introduction to Data-Driven Personas

Automatic Persona Generation (APG) is a system developed by the persona research team at Qatar Computing Research Institute. APG is defined both as a methodology and a system for automatic creation of personas from online analytics data.

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. Continue reading “9 Benefits of Data-Driven Personas”