Speech and text analytics, also known as audio mining, is technology that converts human speech and text into structured data. Speech analytics software scans customer interactions to extract valuable insights, allowing businesses to understand customer sentiments and plan for call center automation.
The technology generates actionable data that can be used to improve future interactions, train contact center agents and target key performance indicators (KPIs). It can be game-changing technology when deployed alongside other advanced call center technologies, such as implementing conversational AI.
Call center speech analytics differs from voice analytics, which delves deeper into customer interactions to analyze customer emotion, intent and sentiment. Here’s a quick comparison of the two technologies and their distinct capabilities:
| Speech Analytics | Voice Analytics | |
|---|---|---|
| Analysis Type | Analyzes the content of audio and textual speech with a focus on the words used. | Analyzes the emotion, intent, sentiment and tone of speech. |
| Technology Purpose | Used to transcribe speech and extract meaningful insight from calls. | Used to interpret customer behavior and emotion. |
| Type of Data Analyzed | Focuses predominantly on structured data, such as text transcribed from customer calls. | Capable of handling both structured and unstructured data, such as features of speech like a caller’s tone, pace of voice, and pitch. |
| Technologies Used | Uses technologies like natural language processing (NLP) and speech recognition. | Uses a broader range of technologies, including AI, biometrics, machine learning and sentiment analysis. |
| Intended Outcome | Aims to help businesses identify keywords, patterns and trends in spoken content. | Aims to help businesses understand customer sentiment and analyze callers’ emotions. |
Speech analytics call center software includes:
The first step in speech analytics is to process conversations between your contact center agents and customers. The technology uses data processing to analyze calls in real time, transcribe and process the conversation and then analyze the resulting data. Speech analytics can also identify keywords, key phrases and patterns to help you evaluate customer satisfaction and reduce customer churn.
Deploying speech analytics across your contact center can help you improve the quality of customer calls and boost agent and customer happiness. The benefits of speech analytics include:
Enhanced customer satisfaction and loyalty
By analyzing every interaction, you gain a deeper insight into customers’ needs and requirements. Building speech analytics into your customer experience allows you to solve callers’ issues quickly and enhance customer loyalty by reducing average handle time.
Improved agent performance and training
Agents typically engage with customers and then document the discussion and any agreed-upon actions. Speech analytics does the hard work for them, analyzing the topics discussed and generating actionable data.
Increased operational efficiency
Call agents can waste hours transcribing calls, trawling through conversations to recap what was discussed and noting required actions. Speech analytics takes this requirement away from your teams, enabling them to focus on what they do best: spending time on the phone with customers.
Reduced compliance risks
Manual processes can cause call agents to forget about agreed-upon actions or contravene agreed-upon data policies. Speech analytics helps you maintain compliance with industry and government regulations and detect and manage sensitive information.
Insightful competitive intelligence
Taking spoken word data in multiple languages and transcribing it into text offers significant competitive intelligence benefits. Analyzing information from recordings can help you better understand what callers are saying, recognize requirement trends and transform customer interactions.
Higher revenue and cost savings
Because speech analytics helps to unburden agents, it enables them to spend their time more efficiently (i.e. answering calls, solving customer problems and promoting sales). As a result, contact centers can enjoy significant time and money savings by deploying the technology.
Most contact centers buy speech analytics tools primarily for 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.
Customer experience optimization
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.
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.
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.
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.
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 in banking
If you asked a banking customer what their biggest complaint was during the height of the global 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.
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 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.
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 voices aren’t being 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.
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 automatically. 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.
Uniphore’s speech analytics technology helps you better understand your customers’ needs. Our U-Analyze solution unlocks actionable insights into every customer interaction, helping you discover potential friction points and areas for agent performance improvement. The voice analytics and AI technology uses the cumulated data from conversations across your contact center to generate upsell and cross-sell opportunities, enhance customer interactions and enhance compliance.
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:
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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