Abstract
Experiences of users determine their actions and therefore have great influence on the business result of service providers. Thus, it is highly important to know and control these experiences. Decisions and actions are most effective if they are based on individual users and their detailed experience history. Currently available methods for measuring user experience fail in providing sufficient detail or continuous availability. This paper introduces a big data analytics method, which predicts every user’s satisfaction with the service provider. This is performed using an analytics algorithm, adding psychological interpretation to the measured and individually perceived user’s quality of experience. The result is a score that enables individualized marketing and allows understanding the cause of dissatisfaction. It is also able to assign a subjective quality score to network assets.
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