Download PDFOpen PDF in browserContact center productivity improvement based on predictive analyticsEasyChair Preprint 20976 pages•Date: December 5, 2019AbstractThe overall performance of a contact center is often measured through its ASA (Average Speed of Answer), abandonment rate and Service Level (SL). This study focuses on the predicting ASA as a function of call volumes, AHT, occupancy of agents, number of productive Full Time Equivalents (FTE) and Off Phone Activities % (OPA) and analyzing the impact of each of these parameters on ASA through sensitivity analysis. An ensembled model for ASA prediction was created using multi-variate time series prediction algorithms like ARIMAX and neural network predictor based on 3 years of data from a contact center in US Keyphrases: Average Speed of Answer, Contact Center, capacity planning, time series analysis
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