Persona Analytics: Implementing Mouse-tracking for an Interactive Persona System

  Using an interactive persona system, user behavior and interaction with personas can be tracked with high precision, addressing the scarcity of behavioral persona user studies. In this research, lead by Soon-gyo Jung and Joni Salminen, we introduce and evaluate an implementation of persona analytics based on mouse tracking, which offers researchers new possibilities for…… Continue reading Persona Analytics: Implementing Mouse-tracking for an Interactive Persona System

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

In this research, my co-researchers and I 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…… Continue reading Customer segmentation using online platforms: isolating behavioral and demographic segments for persona creation via aggregated user data

Making Meaningful User Segments from Datasets Using Product Dissemination and Product Impact

Online companies face large user populations, making segmentation a daunting exercise.  In this research, we demonstrate an approach that facilitates user segmentation. The approach leverages product dissemination and product impact metrics with normalized Shannon entropy.  Using 4,653 products from an international news and media organization with 134,364,449 user-product engagements, we isolate the key products with the…… Continue reading Making Meaningful User Segments from Datasets Using Product Dissemination and Product Impact

Forecasting the Nearly Unforecastable: Why Aren’t Airline Bookings Adhering to the Prediction Algorithm?

Using 27 million flight bookings for 2 years from a major international airline company, we built a Next Likely Destination model to ascertain customers’ next flight booking. The resulting model achieves an 89% predictive accuracy using historical data. A unique aspect of the model is the incorporation of self-competence, where the model defers when it…… Continue reading Forecasting the Nearly Unforecastable: Why Aren’t Airline Bookings Adhering to the Prediction Algorithm?

Too few, too many, just right: Creating the necessary number of segments for large online customer populations

We develop a framework to reduce the number of customer segments to the smallest quantity without losing essential information of the underlying population in the electronic marketplace. We evaluate our approach in a case study using more than 21 million online flight bookings of a major airline company resulting in a 57.5% decrease from 1194…… Continue reading Too few, too many, just right: Creating the necessary number of segments for large online customer populations

Persona Analytics: Analyzing the stability of online segments and content interests over time using non-negative matrix factorization

Personified big data and rapidly developing data science techniques enable previously unforeseen methodological developments for longitudinal analysis of online audiences.  Applying data-driven persona generation on online customer statistics from a real organizational social media channel, we demonstrate how personas can be deployed to understand online customer patterns over time.  We conduct 32 monthly rounds of…… Continue reading Persona Analytics: Analyzing the stability of online segments and content interests over time using non-negative matrix factorization