Simulation-Based Quantitative Persona Design for Life Planning Studies

Abstract

Persona methods are widely used in marketing to create customer-centric services. However, the following issues exist in designing and evaluating personas for services and measures that have characteristics which may benefit customers in the distant future, such as in the domains of asset formation and life planning. First, many analyses are based on previous or current customer attributes, which do not always result in accurate customer classification. Second, identifying the appropriate target group is difficult because the impact of the services and measures provided to each persona is not evident. In this paper, we present an example of persona creation and evaluation that considers the above characteristics, targeting the asset formation domain. This method generates future customers attributes using a social simulation based on real data, understands the effects of measures using scenario analysis in a virtual space, and has aspects as a proposal for improving quantitative persona creation methods. The key findings are that predicting and grasping the possibility of future change in customer attributes and creating personas based on these predictions is quantitatively and objectively possible; moreover, quantitatively grasping the impact of services and policies on customers and prioritizing among the created personas is possible.