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Conversational Analytics is Transforming the Customer Service Industry
Conversational Analytics is Transforming the Customer Service Industry

March 26, 2021

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Most of us 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 analyzed, and insights are extracted from it. The prime reason for this is that it is highly cumbersome to listen to every customer call and extract meaningful insights. That is where conversational 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.

Conversational analytics delivers actionable insights

Conversational 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 conversational 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 to present the analytical findings.

Customer interaction analytics lets brands understand their customers better. It provides actionable business intelligence using Artificial Intelligence and Natural Language Processing engines deployed on customer conversations. It drives better agent performance, regulatory compliance, and customer experience. Conversational analytics converts 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 conversational analytics use cases in contact center

Most contact centers buy conversational analytics solutions, majorly for cost-saving purposes. Cost reduction might be the initial driver, but the 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 conversational analytics solutions are indispensable. Here are some of its top use cases 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 conversational analytics solutions to customer interactions, it is possible to anticipate when and if customers will churn and preclude such actions. 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 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 conversational analytics. The 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. Conversational 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 conversational 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. Conversational  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. Conversational 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.

By Santosh Iyer, Chief Business Officer, Uniphore

 


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