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Wednesday, August 15, 2018

3 Ways to Boost Call Center Efficiency with Speech Analytics

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Speech analytics solutions have helped users tackle a number of contact center business challenges over the years, including cost containment, risk mitigation, more streamlined customer experiences, and the identification of process and product gaps. New advances such as automation, artificial intelligence, and machine learning are helping organizations leverage their speech analytics solutions even further.

Let’s look at how speech analytics can give even more power to these three solutions.

Automate Quality Management with Speech

Quality management solutions have been widely used in contact centers to listen to and assess the quality of the interactions taking place, but not without issues. While QM solutions are effective, there’s always the possibility of running into issues such as statistical validity, scoring inconsistency and lack of objectivity.

This is where speech analytics comes into play. Automated quality management solutions overlay the transcription capabilities from speech analytics with rule building and evaluation to automate some or all of an organization’s quality form. Doing so can help increase the confidence level associated with quality data while freeing up coaches to coach and delivering more consistent, unbiased feedback to agents.

Power Predictive Analytics with Speech

Predictive Analytics is a key tool in understanding and driving business outcomes. But in order to predict outcomes successfully, extensive and varied data is needed. How can you retrieve this sort of data, though? Through conversations that agents have with customers, speech transcription can be integrated into any organization’s activities for enhanced predictive power.

Enhance Robotic Process Automation with Speech

Robotics technology is the latest and greatest—changing the way we work today. In the contact center world, software robots can provide employees with guidance and assistance on handling or fully automating tasks, and executing them repeatedly at high levels of accuracy.

Virtual assistants (VAs), a robotics application, is used to respond to simple natural-language inquiries and requests, as well as engage in dialogue with customers. In order to get the most effective benefits from your VAs, it is important to define and refine VA responses—speech transcription can help you achieve this.

For example, an emerging trend in the marketplace can be quickly identified by analyzing voice conversations, then applying intelligence to adjust VA responses and guidance.

Overall, using speech analytics solutions to power artificial intelligence, automation, predictive analytics, and big data can help you make more effective use of skilled talent by redirecting resources away from automated tasks toward value-added activities that drive better outcomes.

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