Speech Analytics In Quality Assurance

Speech Analytics is not the thing that should be keeping Quality Assurance & Monitoring professionals up at night. It shouldn’t even be among the top five things that keep them up at night.

While Speech Analytics applications provide unprecedented access to previously untapped intelligence in calls, the way these technologies work and their existing limitations make Speech Analytics applications far more valuable when pointed toward other use cases – customer satisfaction, customer and agent retention, call center efficiency, call driver understanding, repeat call patterns, call deflection opportunities, assessment of digital channel performance, identification of processes in need of re-engineering, and more.

You can also get more information about the Best Speech Analytics solutions online.

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Speech Analytic applications have robust capabilities that leverage AI and Machine Learning to understand the relationship between words uttered and uncover conversational topics, understand human emotion (sentiment) being expressed, and even leverage data about the customer and predictive analytics to identify likely outcomes.

However, Speech Analytics applications on the market today do not have the sophisticated logic trees that would be required to follow and assess whether an agent conducted the correct troubleshooting steps or due diligence to uncover sales needs, which is challenged by the nuances and cultural variations in human interactions and is ultimately limited to the spoken word.

Imagine a sales queue in which an agent needs to ask a series of questions to uncover customer needs, reference the answers to those questions against a regional pricing matrix in a knowledgebase article, and also take into consideration a competitor’s promotion or monthly budget communicated by the customer earlier in the conversation.