What is speech analytics and how does it benefit businesses?

Speech analytics is the process of extracting meaningful insights from calls in order to improve future conversations. One of several speech technologies, speech analytics scours audio interactions—either in real time or through voice recordings—for useful contextual data, such as customer feeling, sentiment and more. Combined with artificial intelligence, speech analytics can then generate actionable data that businesses (particularly within the call center space) can use to fine-tune future interactions and improve key contact center KPIs. (You can find an expanded speech analytics definition here.)

Call center speech analytics uncovers valuable hidden data.

We all have heard the familiar line, “this call may be recorded for quality assurance and training purposes,” when we call a customer care number. But the reality is only about 1% of the recorded calls in a contact center are analyzed and insights are extracted from it. The reason: it is highly cumbersome to listen to every customer call and extract meaningful insights. That is where call center speech analytics comes into the picture. Imagine the business potential if 100% of customer calls—across traditional and digital channels—could be scrutinized and their findings documented. That would be a treasure trove of information that customer service industry leaders would love to get their hands on.

Speech analytics delivers actionable insights.

Speech analytics (also referred to as audio mining) identifies human speech and text via automated speech recognition and converts that into data. The data is then structured so actionable insights can be drawn from it. In its most basic form, a speech analytics solution consists of a speech recognition engine that converts speech to data, an indexing layer that searches the information, a query engine that lets users query the data and, finally, a reporting application that enables you to present the analytical findings.

Customer interaction analytics lets brands understand their customers better. It provides actionable business intelligence by deploying AI and NLP engines to customer conversations in multiple digital channels. Organizations can leverage this data to look for emerging trends, topics driving customer calls and customer friction points as well as for improving agent performance, regulatory compliance and strategic planning and decision-making.


What are the top speech analytics use cases in contact centers?

Most contact centers buy speech analytics tools for primarily cost-saving purposes. While cost reduction may be the initial driver, speech analytics solutions offer so much more—adding significant value in agent quality improvement, business process optimization, litigation avoidance, customer satisfaction improvement and revenue augmentation. In today’s data-driven world, speech analytics solutions are indispensable for making smarter decisions across a range of business cases. Here are some of the top use cases of speech analytics solutions in contact centers.

Speech analytics use cases

1. Customer experience

Nothing is more critical in the customer service industry than delivering a great customer experience. Customer interaction analytics sheds light on what customers want, how agents can provide a better experience and what actions might damage a customer relationship. By applying speech analysis to customer interactions in traditional and digital channels, it is possible to anticipate when and if customers will churn and preclude such actions. With the help of AI, it can pick up on customer emotions and sentiments and document what drives customers away from a brand. That can help brands improve customer experiences—and, consequently, customer satisfaction—plug customer service loopholes and course-correct detrimental actions before it is too late.

2. Quality management

Quality management is critical to contact centers. However, the process of ensuring that agents perform optimally and customers are properly serviced has traditionally been labor intensive. That changed with the advent of modern speech analysis technology. Today, contact center speech analytics software ensures that calls are classified accurately and pre-selected calls are forwarded to supervisors for evaluation and quality assurance. This streamlines the work of quality assurance personnel and even adds intelligence to the entire quality management process in a contact center.

3. Operational efficiency

Improving operational efficiency is another primary goal for any contact center. This includes improving key contact center KPIs that reduce operating costs in terms of money, time and effort. Speech analytics tools provide insights into customer calls and help streamline operations by improving future customer interactions. By diligently classifying calls, uncovering hidden insights, exposing patterns and discovering relationships beyond human cognition, speech analytics offers detailed root cause analysis of customer issues—without burdening call center staff. As a result, speech analytics lets organizations revamp their operations, cut down on redundant overhead costs and improve ROI in contact centers.

4. Revenue generation

Building a predictable and growing revenue engine is the goal of every business. Speech analytics tools can help organizations boost sales by refining sales techniques, providing real-time alerts to agents to exploit a sales opportunity and overcoming customer objections with hard data. Speech analytics software can build an exhaustive correlation between call drivers and outcomes. That kind of mapping between customer conversations and sales conversions is pure gold in a contact center scenario. It can help agents maximize their efforts strategically in sales conversations that offer the best sales conversion rates.

Real time speech analytics solutions help top industries.

Speech analytics solutions—particularly real time speech analytics solutions—are helping today’s banking, insurance, telecom and BPO industry leaders improve their strategic outcomes and drive customer satisfaction. Here’s how:

speech analytics use case

1. Speech analytics in banking

If you asked a banking customer what their biggest complaint was during the height of the COVID pandemic, odds are it would be the inability to talk to a human agent. Most banking contact centers were inundated with customer calls leaving them helpless to provide the right customer service.

Today, many still struggle with unsustainably high call volumes. Speech analytics in banking can help change that. Thanks to Natural Language Processing (NLP), banking speech analytics solutions can help human agents understand the customers better and even anticipate their needs.

For those banking calls that need human attention, speech analytics solutions can help too. Real time banking speech analytics software can provide human agents with the right in-call assistance, alerts, notifications and more. This includes empathy prompts based on real time emotional data. Thus, banking speech analytics solutions make it possible to drive a superior customer experience and build long-term banking relationships.

Lastly, speech analytics banking solutions can provide hitherto unheard insights into reducing customer call volumes, achieving first contact resolution (FCR) and reducing average handle time (AHT). As a result, banks and financial service providers that use predictive speech analytics banking software gain an upper hand over industry disruptors—such as fintechs and neobanks—out to poach legacy banking customers with better customer service. By predicting customer behavior and guiding banks in implementing the right corrective actions in advance, artificial intelligence, automation and speech analytics can significantly reduce customer defection and churn.

2. Speech analytics in insurance

Insurance is a sector that faces a huge number of challenges. In response to increased competition, tighter regulation and bigger customer expectations, the insurance industry is undergoing a period of rapid digital transformation.. Insurance providers looking to differentiate themselves should consider augmenting their customer service capabilities with speech analytics software. Insurance speech analytics can go a long way in helping meet customer expectations and ensuring insurance players can grow rapidly.

Speech analytics in insurance lets you monitor and analyze customer conversation data to anticipate customer needs, improve compliance, reduce fraud, lower costs and deliver a better customer experience. Insurers spend ample time and money to keep customer support up to date. With speech analytics in insurance, it is possible to create structured responses based on past customer interactions. What’s more, insurance speech analytics solutions can support insurance contact centers to handle multiple customer-facing processes.

Insurance speech analytics software can also help human agents with the necessary real-time assistance, understanding the real intent of the customers, automating mundane and repetitive tasks and ensuring that agents comply with the regulations and disclosure norms set forth by various governing bodies. Thus, speech analytics in insurance can render the agents free to do what they do best – empathize with the customers. In fact, top insurance players are already implementing conversational AI and speech analytics software to improve throughput, efficiency and insurance customer service delivery.


3. Speech analytics in telecom

Telecom speech analytics solutions are revolutionizing the telecom sector, which is finding it increasingly difficult to cater to customers’ rising demands. By using machine learning to fully understand human conversations, telecom speech analytics solutions can help resolve customer queries quickly and satisfactorily. This is important because telecoms face one of the highest churn rates of any industry. The chief reason being customers feeling their voice not getting heard by the brand. Thanks to modern predictive analytics, today’s speech analytics telecom solutions enable service providers to anticipate customer problems and take corrective actions before it inconveniences the customer.

Because telecom speech analytics tools are powered by AI and machine learning, they are context aware. This makes such solutions highly desirable to telecoms faced with a deluge of customer calls. With the right speech analytics telecom technology, it is possible to leverage pre-built telecom intent models to upgrade telecom customer experiences. By delivering easy, personalized conversations, telecom speech analytics solutions can simultaneously drive customer satisfaction and loyalty while reducing telecom customer churn.

Lastly, AI-powered telecom speech analytics solutions can help telecom players predict if a customer is likely to pay or not and find the optimal way to approach individual customers on billing and other account-related actions.

4. Speech analytics in BPO

The BPO industry is seeing increased deployment of technology tools—including BPO speech analytics solutions—to help contact center agents understand their customers better. Since speech analytics BPO solutions understand human speech, they are ideal for use in AI-based chatbots. For queries that are too complex for chatbots to handle, the technology can escalate the customer to live agent assistance using Robotic Process Automation (RPA). Here, speech analytics BPO technology driven by AI can identify the customer’s real intent in real-time and offer suitable alerts to the agent. And because real time speech analytics BPO solutions can monitor 100% of the customer calls, they can derive actionable insights, raise red flags when there are areas of concern, assist during agent QA process and more.

Speech analytics BPO software can also assist in training BPO agents with domain knowledge, analyzing call disposition across multiple tags and increasing first call resolution. BPO speech analytics tools can continuously monitor agent performance and send the right feedback to supervisors in real-time. They can even help BPOs in adhering to regulatory compliance in the BPO industry.

Lastly, real time speech analytics solutions can help alleviate a longstanding BPO pain point: manual, front-office tasks that sap agent attention and empathy towards customers. Luckily, speech analytics BPO tools can streamline these burdensome processes and help BPOs adhere to the business and customer metrics that matter.

Learn how Uniphore’s speech analytics solution can help you transform your contact center.


One of several speech technologies, speech analytics is the method of understanding customer calls or text with an aim of extracting valuable insights from it. Speech analytics is mostly used by customer service organizations in their contact centers. It lets brands improve their customer service and uncover valuable information about the customers.

Speech analytics offers huge benefits for customer support call centers. Here are the top advantages:

  • Understand the customers and their problems better
  • Learn about their real intent and anticipate their needs
  • Improve the quality of support provided using customer data
  • Streamline processes and reduce the cost of running a call center
  • Uncover insights and discover new business opportunities
  • Provide better on-boarding and training for call center agents
  • Get a better sense of the issues with the products offered.

In its most basic form, a speech analytics solution consists of a speech recognition engine (i.e. automated speech recognition) that converts speech to data, an indexing layer that searches the information, a query engine that lets users query the data, and finally, a reporting application that enables you to present the analytical findings.

As the names suggest, real time speech analytics helps contact center agents as the call is progressing while post call analytics helps to uncover insights after the call has ended. Real time speech analytics helps agents strive for first call resolution. Post call analytics helps you improve your contact center processes and provide better upskilling and training for the contact center agents.

Speech analytics helps businesses learn about the issues that customers are facing and provide them with a better experience. Speech analytics helps to determine customer emotions, sentiment and implied needs. With the right application of speech analytics, brands can improve customer service—and, consequently, customer satisfaction—plug customer service loopholes and course-correct detrimental actions before it is too late. It also helps the contact centers to better equip themselves to resolve customer queries and optimize the overall customer experience.

Voice analytics is about analyzing the spoken or acoustic data while speech analytics includes both spoken and text-based data. The benefit of pure voice analytics is that you can learn a lot of about what the customers are saying, how they are saying it and what they mean. Voice data is all about intonation, modulation and other aural cues that help to better understand customers. Voice analytics includes elements of syllable emphasis, the tone, the pitch of the voice and even the tempo to understand customer needs. Speech analytics is more straightforward, making it easier to analyze.

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