Model of a Personalization-Based Agent System for Early Product Adoption Phases

Businesses that offer Software-as-a-Service (SaaS) often allow a "tryout" phase to immediately test their system. The loss of control during this phase forces providers to offer simple ways of product learning for the demonstration of product features. We therefore develop a model of a hybrid personalization agent and logic, which is able to match predefined actions to the specific users' needs to enhance product learning. The logic communicates the selected action to an IT-agent system that subsequently executes the action. By applying this model, businesses obtain a competitive advantage by regaining the possibility to assist and influence the user in the product adoption process. We construct our work on a product adoption process and customer lifecycle model as well as the research areas of usability and technology acceptance research to depict ways of interactive learning support. Indicators are monitored which are finally utilized to enhance the attribute "easy to learn".