- Top speech analytics use cases
- How Speech analytics solutions help top industries?
- Speech analytics in Banking
- Speech analytics in Insurance
- Speech analytics in Telecom
- Speech analytics in BPO
We all have heard the familiar line, “this call may be recorded for quality 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 analysed, and insights are extracted from it. The chief reason for this is that it is highly cumbersome to listen to every customer call and extract meaningful insights. That is where speech analytics comes into the picture. Imagine the business potential if 100% of the customer calls are scrutinized and the 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 is also referred to as audio mining. It is a technology that identifies human speech and text 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 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 using AI and NLP engines deployed on customer conversations. It drives better agent performance, regulatory compliance, and customer experience. Speech analytics converts your unstructured conversational data into an auditable pattern. Organizations can leverage this data to look for emerging trends, topics driving customer calls, identifying customer friction points, improving agent performance, planning for operational overhaul, and supporting strategic decision-making.
Top speech analytics use cases in contact centers
Most contact centers buy speech analytics solutions, majorly for cost-saving purposes. Cost reduction might be the initial driver, but speech analytics solutions do not stop there. It helps in agent quality improvement, business process optimization, litigation avoidance, customer satisfaction improvement, and revenue augmentation. Today, contact center leaders realize that there is a better way to decision-making than the traditional way of making decisions that do not factor in the data. Hence speech analytics solutions are indispensable. Here are some of the top use cases of speech analytics solutions in contact centers.
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. With the right application of speech analytics solutions to customer interactions, 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, plug customer service loopholes, and course-correct detrimental actions before it is too late. All this comes from listening to the voice of the customers, and speech analytics software helps you do just that.
2. Quality management
Quality management cannot be overemphasized in a contact center. The traditional labor-intensive functions of ensuring agents perform optimally and customers are serviced right got a major overhaul with speech analytics. Speech analytics software in a contact center ensures that calls are classified accurately, and pre-selected calls are forwarded to supervisors for evaluation and quality assurance. It 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 and reducing operating costs is another primary goal for any contact center. Speech analytics solutions provide insights into customer calls and help streamline operations by improving future customer interactions. Root cause analysis of customer issues gets a shot in the arm thanks to speech analytics diligently classifying calls, uncovering hidden insights, exposing patterns, and discovering relationships beyond human cognition. It 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 solutions 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.
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How speech analytics solutions help top industries
Let’s now delve into how speech analytics solutions help some major industry verticals like banking, insurance, telecom, and BPO sectors.
1. Speech analytics in Banking
If you asked a banking customer during the height of the COVID pandemic, one of their biggest complaints was not being able to talk to a human agent. Most of the banking contact centers were inundated with customer calls leaving them helpless to provide the right customer service. Speech analytics in banking can help to change all that. Banking speech analytics solutions can assist human agents, thanks to Natural Language Processing (NLP) capabilities. It helps to understand the customers better and even anticipate their needs due to the latest advancements in banking speech analytics software solutions.
For those banking calls that need human attention, speech analytics solutions can help too. Banking speech analytics can provide human agents with the right in-call assistance, alerts, notifications, and more. Thus, it is possible to drive a superior customer experience. Human empathy is the most significant factor in building long-term banking relationships, and banking speech analytics solutions help to do just that.
Speech analytics banking solutions can also provide hitherto unheard insights into reducing customer call volumes, achieving first contact resolution (FCR), and reducing average handle time (AHT). Predictive speech analytics banking software does play a significant role in the banking and financial services sector since there is a constant threat from upstart and nimble fintech players that can poach the legacy banking customers overnight with better customer service. AI, automation, and speech analytics can significantly reduce customer churn by predicting customer behaviour and guiding the banks in implementing the right corrective actions in advance.
2. Speech analytics in Insurance
Insurance is a sector that faces a huge number of challenges. Due to the increased competition, higher regulation, and bigger customer expectations, the insurance industry urgently needs help and conversational AI technology can help. Customer service is one aspect where the insurance industry could look at speech analytics to bring about a positive change. 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, to be better equipped to 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. Insurance speech analytics solutions can support insurance contact centers to handle multiple customer-facing processes.
Insurance speech analytics software can help human agents with the necessary real-time assistance, understanding the real intent of the customers, automating mundane and repetitive tasks, and ensuring that the 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. 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’ needs of late. Telecom speech analytics solutions can help to resolve customer queries quickly and satisfactorily thanks to machine’s ability to understand human conversations using ML. It is a fact that 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. Speech analytics telecom solutions can help to address the problem. Thanks to predictive analytics, it is possible to anticipate customer problems and take corrective actions before it inconveniences the customer.
Telecom speech analytics solutions are powered by AI and Machine Learning and hence they are context aware, making such solutions highly desirable to telecoms that are facing 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. Delivering easy, personalized conversations your customers will love, is vital to reducing telecom customer churn. Telecom speech analytics solutions help you do just that.
Knowing if a customer is likely to pay or not, finding the optimal way to approach an individual customer, are all crucial for any telecom player. The AI-powered telecom speech analytics solutions can be of immense help in such scenarios too.
4. Speech analytics in BPO
The BPO industry is seeing increased deployment of technology tools to help contact center agents understand the customers better. BPO speech analytics solution is one of them. Since speech analytics BPO solutions understand human speech, they are better suited to resolve simpler customer queries using AI-based chatbots. Speech analytics BPO technology driven by AI can now identify the customer’s real intent in real-time and offer suitable alerts to the agent. Speech analytics BPO solutions can now monitor 100% of the customer calls, derive actionable insights, raise red flags when there are areas of concern, assist during agent QA process, etc. Thus conversational AI-driven solutions are truly disrupting BPO’s voice business.
Training the BPO agents with the domain knowledge, analyzing call disposition across multiple tags and increasing first call resolution can all be realized with speech analytics BPO software. The agent performance can be continuously monitored with BPO speech analytics tools, and the right feedback be sent to agent supervisors in real-time. It improves the overall call quality and even helps BPOs in adhering to regulatory compliance in the BPO industry.
BPOs for long have been struggling with manual operations of front-office tasks. It led to agent fatigue and inability to focus on customer problems and ultimately leading to lack of empathy towards customers. Luckily, speech analytics BPO tools can help to streamline the 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.
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 benefits:
-- 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 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.
As the names suggest, real-time 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 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 to 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, 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 the 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. Hence analyzing it is easier, but voice analytics is more valuable.