• 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.


What is Speech Analytics? FAQs

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.

What are the benefits of speech analytics for Customer Support call centers? FAQs

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.

How does speech analytics work? FAQs

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.

What is the difference between real-time vs post-call speech analytics? FAQs

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.

How to optimize customer experience with speech analytics? FAQs

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 Vs Speech Analytics: What are the key differences? FAQs

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.

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