Call centers across the country measure a lot of different metrics to assess their overall performance and to create goals for the next quarter. But, which metrics are the most profitable for your call center and industry? And, which of these profitable metrics can be improved with predictive voice analytics?
It sounds fantastic, like something out of a science-fiction story. But, predictive voice analytics software can assess how likely a given debtor is to pay after initial contact, and rank all of your first contacts by likelihood of payment on a follow-up call.
Contact centers in the sales and collections industries are constantly on the lookout for ways to improve their key performance metrics. To this end, many contact center managers invest in tools such as speech analytics, survey systems, and other quality/performance assessment resources. How could such a predictive analytics program drive your contact center forward?
How can collection agency call centers successfully manage the high-volume of interactions between customers and phone agents on a daily basis? Through the use of a Predictive Voice Analytics software.
Machine learning algorithms and predictive models can be hugely beneficial to call center leadership, helping with everything from automating the Quality Assurance process to identifying agents in need of more training, to predicting the future behavior of your customers.
Collection agencies face a constant uphill battle to collect on delinquent receivables for their clients. Whether you’re collecting credit card debt, telecom debt or student loans, meeting collections goals can be tough.
Deep learning seems to be a natural means to delivering high quality signal-based voice analytics. Consider the cocktail party effect: given many different sources of noise, the human brain is able to process all of them and focus one’s auditory attention on a particular source (a person speaking for instance), and further be able to discern what the person is saying, interpret it, and react accordingly. With deep learning methods, machines are now able to emulate the same activity and more.
RankMiner is an automated, easy to use, predictive analytics solutions for call centers. RankMiner identifies voice-based emotions and behaviors from agent & customer conversations. Using machine-learning algorithms we transform unstructured data into valuable and prescriptive information for Call Centers.
The Future of Call Center Analytics
Machine Learning, emotional voice analytics and predictive modeling are converging to revolutionize how call centers enable their agents and interact with customers. Analyzing the voice recordings captured from each call, Call Centers will now enable agents to perform more effectively during the call, allowing agents to adjust communication style and gain emotional intelligence., and Management to predictive agent & customer behaviors and the associated outcomes.