Carmit DiAndrea, VP Portfolio Market Strategy, Verint
Explosive growth in speech analytics adoption over the past decade has solidified its standing as a competitive differentiator. Today, best-in-breed speech analytics solutions are highly accurate and can proactively identify emerging trends, conversational topics, and relationships between topics; discern customer emotion; reveal root cause; and automatically get the right data into the right hands at the right time. With these sophisticated functionalities, speech analytics users have successfully tackled many of the technology’s intended contact center uses, including:
- Cost containment
- Risk mitigation
- Design of better, more streamlined customer experiences
- Identification of process and product gaps
However, advances in automation, artificial intelligence, machine learning, and big data are extending the ways speech analytics can be leveraged to address an expanding set of business problems and opportunities.
Central to each of the scenarios below is how speech analytics creates accurate, speaker-separated transcripts of voice interactions, why that matters, and what it means for today’s employees, customers, and businesses.
Automated Quality Management
– Quality management, one of the contact center industry’s most widely deployed practices, requires listening to and manually assessing the quality and content of phone conversations between customers and agents. This practice is plagued with issues of statistical validity, scoring inconsistency, and lack of objectivity—not to mention the tension of balancing time spent on scoring with time spent driving improvement through coaching. Automated quality management solutions overlay transcription capabilities from speech analytics with rule building and evaluation to automate some or all of an organization’s quality form. These solutions can increase the confidence level associated with quality data while freeing up coaches to coach and delivering more consistent, unbiased feedback to agents.
– Enabled by increasing processing speed and capacity, predictive analytics has grown into a fundamental tool for understanding and driving key business outcomes. But successfully predicting key outcomes (such as ability to upsell or retain customers or identify the likelihood that a customer in arrears will pay) requires extensive and varied data. The conversations that agents have with customers provide a rich data set that, through speech transcription, can be effectively integrated into any organization’s activities for enhanced predictive power.
Robotic Process Automation
– Robotic process automation—a set of solutions that automate or assist in processes executed by humans—can be made even more effective when combined with artificial intelligence. Software robots can provide employees with guidance and assistance handling tasks or fully automating tasks, and execute them repeatedly at high levels of accuracy, typically at speeds beyond human capabilities. Virtual assistants (VAs) are the fastest-growing application of robotics in contact centers, responding to simple natural-language inquiries and requests, and engaging in dialogue with customers. Transcripts of conversations that customers have with employees are used to define and refine VA responses. 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.
Transcription is transforming the way leading organizations do business, enriching artificial intelligence, automation, predictive, and big data activities. All of this translates into the ability to make more effective use of skilled talent by redirecting resources away from automated tasks toward value-add activities that drive better outcomes.
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