What is conversation analytics?

Conversation analytics can be succinctly described as the computerized study of voice and text-based interactions, such as in phone calls and recordings, live chat, emails, SMS, and other communications. 

As a field of study, conversation analysis has allowed researchers to explore the intricate framework that defines human interactions. Delving into the details of conversation has revealed deceptively simple building blocks from which all interactions are made. By dissecting expressions in such a way, researchers laid the groundwork for computer-aided conversation analytics to sort phrases by sentiment, identify trends and more. 

Conversation analytics now represents near-limitless potential for corporations looking to understand their customers on a deeper level. However, getting the most out of this powerful technology involves understanding what it is, what it can do and why it might matter for your business. 

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How does conversation analytics work? 

The processes employed in conversation analytics stem from natural language processing (NLP), which is a multidisciplinary field combining linguistics, computer science, artificial intelligence, and machine learning. 

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NLP aims to help computers understand human interactions, whether in written text or spoken aloud. Conversation analytics leverage advances in NLP to pull mission-critical insights from conversations for enterprise use.  

Unlike speech analytics, which deal more generally with spoken interactions, conversation analytics focus on understanding interactions in context – between participants – across channels. This yields several important benefits for companies and contact centers, in particular. 

Benefits of conversation analytics 

Improving the customer experience lies at the heart of every competent business plan. 

Forward-thinking organizations around the world fine-tune their development goals to their customers' needs. However, they must truly understand their customers in order for this approach to work. 

Conversation analytics open the door for customers' needs and general sentiment to shine through and be acted upon by employees in direct contact with them and higher-ups in the organization as well. With 67 percent of customers reporting a willingness to pay more for better service, the use of accurate conversation analytics might not be optional. Here are a few benefits of conversation analytics: 

• Identifying emotions: Expressing real empathy for customer concerns and adapting to their emotional states can completely change the result agents get in dealing with them. Conversation analytics can highlight salient emotions as a conversation is underway and in retrospect, allowing agents to better understand how customers may be feeling over time. 
• Improve customer experience: By having a deep understanding of your customers’ wants, needs, and emotions, you can fine-tune every interaction throughout the customer journey to improve customer experience and customer satisfaction.  
• Reduce customer churn: By monitoring and identifying trends in customer behavior, you can identify customers who are at risk and take proactive action to restore customer satisfaction and prevent churn.   
• Drive product development and innovation: Conversation analytics helps you identify your customers’ most common pain points, discover the services or features they want most, and leverage that intelligence to inform product development, and inspire new product innovation.  
• Optimized marketing and sales strategies: With insights from conversation analytics, you can identify what matters most to your customers and fine-tune your marketing and sales strategies to target their interests with precision.  

Conversation analytics use cases 

Conversation analytics is a versatile tool with many potential use cases, such as:  

• Training call center agents: Training agents to handle specific scenarios becomes much easier when conversation analytics are used as well. Situations that may have been troubling for live agents to recognize and adapt to can be analyzed in greater detail to identify an appropriate way of handling them. 
• Predicting behavior: Many companies have begun focusing their efforts on identifying trends in customer behavior as they develop to better suit their needs in advance. Conversation analytics make this possible on an interaction-by-interaction basis, yielding results that are also applicable to wider business goals. Conversation analytics help highlight trends by cross-referencing keywords and emotional content with other details. This can help in creating better call center scripts for agents to follow, optimizing behavioral profile pairing and more. 
• Real-time agent coaching: Real-time training and coaching has proven to be more effective for improving agent performance than most other approaches. With highly accurate conversation analysis, companies can continuously monitor agents and make relevant suggestions to improve the outcome of any interaction. 
• Identifying security risks: The cost of cybercrime is expected to reach $8 trillion in 2023, rising to a projected $10.5 trillion by 2025. The importance of utilizing effective countermeasures across touchpoints is impossible to overstate. It is possible to mitigate potential lapses in security, even in real-time, by employing conversation analytics. As a conversation progresses, agents can be alerted of potential risks automatically. With CallMiner Eureka, you can identify potential risks, fight fraud and protect your brand’s reputation.  
• Complying with regulations: Compliance with local and international regulations is a major factor in many industries. From PCI-DSS and GDPR rules to HIPAA-derived guidelines, the unique combination of practices your company must abide by to remain compliant can confuse employees as they attempt to resolve customer issues. Live suggestions attuned to each conversation can help avoid costly missteps. 

Frequently asked questions 

Why is it important to analyze

An in-depth understanding of your customers is vital for every business to stay ahead of the competition. With customers interacting with brands across multiple channels, such as phone, chat, email, and social media, omnichannel customer analytics is the key to eliminating data silos and analyzing data from multiple channels simultaneously, adding valuable context to your data.  

How does conversation analytics improve business KPIs?  

From the call center to your sales and marketing departments, conversation analytics provides detailed analysis of your customers across the entire customer journey. Leveraging this data enables you to create precision-targeted sales and marketing campaigns, improve call center agent performance, improve call center quality assurance, reduce risk and aid compliance, and more.  

How does conversation analytics work?  

Conversation analytics eliminates data silos to monitor solicited and unsolicited feedback, including unstructured feedback that’s traditionally difficult to analyze. By leveraging AI (artificial intelligence) and ML (machine learning), it uncovers patterns and trends, predicts customer behavior, and provides actionable insights to improve business performance across the enterprise.