Speech Analytics: Definition, Types, and Benefits

Analyzing calls can give you great business insights, but how many calls can you manually analyze without speech analytics tools? Even if you say 10%, you must have a high budget to operate the contact center. This means that most audio calls are left out unanalyzed.  

Can you imagine how much value this unattended audio data can generate if you have a proper analytics system? 

What is Speech Analytics?

Speech analytics is a process of processing, understanding, and analyzing human speech through artificial intelligence. Contact Centers leverage Speech Analytics to transcribe audio calls and derive powerful business insights, various trends, and key metrics.  

Speech Analytics can understand the meaning, intent, and sentiments involved in the speech, not just spoken words. It uses technologies like ASR (Automatic Speech Recognition) and Natual Language Processing (NLP) to understand conversations

How Does Speech Analytics Work?

Speech analytics involves a multi-step process of turning unstructured audio data into structured data that can be searched and analyzed.  

The first step involves extracting conversations and metadata (information like which agent had the conversation, on what day or time the conversation happened, and who the customer was). 

Next, ASR(Automatic Speech Recognition) converts speech into text. It also extracts and transcripts acoustic signals such as agitation and silence.  

Finally, speech analytics analyzes the conversations, and based on different analyses – such as keyword spotting, tonality-based sentiment analysis, and silence/pause analysis – it tags and categorizes the calls. It gives valuable insights into call quality, Customer Satisfaction (CSAT), customer behavior, and agent performance. Also, for compliance purposes, speech analytics redacts the conversations. 

Types of Speech Analytics

Real Time Speech Analytics

Real time speech analytics analyzes ongoing customer calls and provides the agent with actionable insights or suggests real-time answers. If the agent faces some problem while talking to a customer, relevant information or guidance pops up on the screen. This leads to a better customer experience. 

Post-Call Speech Analytics

As the name suggests, post-call speech analytics analyzes conversations that have already happened. In other words, it performs analysis on recorded calls. It provides valuable insights, patterns, and trends. 

Benefits of Speech Analytics

Review Up to 100% Of Calls

Typically, quality assurance teams can review only a limited number of calls per month - a couple of calls for each agent. But now, with speech analytics, you can automatically review all of your calls. 

Monitor Key KPIs

Speech analytics helps you monitor important KPIs, such as what is MTTR (mean time to resolve), how many calls were escalated to supervisors, and how many compliance violations are happening. 

Enhance Agent Productivity

Based on insights received from speech analytics, provide immediate feedback to agents. Also, enable personalized training of agents based on their weak points. 

Improve Operational Efficiencies

Through monitoring important KPIs, you can better understand inefficiencies and rectify them. Also, you can leverage insights to better plan your future contact center strategies. 

Increase CSAT Scores

Thanks to sentiment analysis, you can understand what actions create a positive customer experience and what makes them frustrated. This helps you better plan your customer experience strategy. 

Summary

In today's time where "data is the new oil," it is unwise to leave more than 90% of calls unheard and unanalyzed. This is why more and more contact centers are adopting speech analytics to derive valuable, actionable insights into customer behavior, agent performance, and compliance. 

If you want to learn more about speech analytics or want to see how it looks in action, reach out to us at connect@floatbot.ai