Along with recognizing and identifying the key drivers of satisfaction, it is also critical to predict customer issues to be able to prevent them from happening, wherever possible. Analytics are an essential element in being able to predict customer issues, proactively connect with individual customers resolve to their issues, and anticipate issues faced by customer that has purchased a new product.
State space algorithms are powerful tools in customer issue prediction. A branch of machine learning, state-space models are able to predict customer issues by learning from different events, customer characteristics, and recent behavior to enable proactive handling of the issues. Based on this insight you can understand the likelihood of different customers reaching out to the call center and how this relates to certain events.