Before revision:  Finally, we use our models to predict the future level of activity within a given conversation, through which we find that the bivariate Hawkes processes that incorporate the amount of information provided by each party or the sentiment expressed by the customer give us the most accurate predictions .
After revision:  Finally, we use the proposed models to improve upon routing algorithms used in contact centers. We show how an activity-based dynamic routing based on predicted information easily computed from our models can outperform well-known and widely used concurrency-based routing rules and substantially reduce customer waiting time, demonstrating how these history-dependent stochastic models can improve operational decision making in practice .