The Rise Of Conversational Analytics

It’s no secret that data is crucial to any intelligent business decision. In the contact center environment, companies are constantly generating huge amounts of valuable, insightful data, from calls, chat conversations, emails, and text messages.

Every piece of information collected by a company during an interaction with a customer has potential value. Yet the majority of the data contact centers have access to remains untouched, hidden in complex call recordings and logs. The reason for this is conversational data is often complex, unstructured, and difficult to analyze. In the past, speech analytics was considered a labor-intensive and time-consuming process, reserved only for the brands with the biggest budgets.

This means smaller companies have frequently missed out on the benefits of advanced analytics, such as reducing handling times by up to 40%, increasing self-service rates by 20%, and boosting conversion rates by up to 50%. Fortunately, newer, more accessible tools built for “conversational analytics” could have the answer.

What are Conversational Analytics?

Expected to reach a value of $6.6 billion by 2028, conversational analytics is a branch of AI-powered technology gaining fantastic popularity in the CX space. Conversational analytics tools extract usable data from human speech and conversations. They do this by leveraging AI to extract and organize information, and Natural Language Processing to “understand” human context.

Originally, these tools were offered as stand-alone solutions for companies looking to gain extra value from their business data. Companies could purchase innovative AI tools capable of analyzing speech, voice, and text, as well as customer sentiment and intent.

However, as demand for consumer insights has increased, conversational analytics tools have also become more accessible. Many leading CCaaS vendors now include conversational analytics tools within the reporting suite for the contact center.

There are also service desk applications, CRM (Customer Relationship Management) services, and workforce management tools with similar functionality. Using convenient NLP programs, vendors can embed the intelligence companies need to understand customer conversations into their existing tools for Customer Experience, leading to better end-to-end visibility of the consumer journey.

In some cases, conversational analytics tools can even be embedded into the UCaaS environment, to help companies collect data about employee engagement and performance, or guide leaders towards strategies for better staff training.

How Do Conversational Analytics Benefit Companies?

Ultimately, conversational analytics are a way for companies to gain a competitive edge with the power of data. They unlock the hidden meaning and insights behind conversations, and make it easier to track valuable trends and opportunities in the business environment.

Used correctly, conversational analytics can:

• Provide insights into the customer journey: With conversational analytics, companies can better understand each stage of the customer journey, and the intent, sentiment, and needs of their customers at each touchpoint. This opens the door to better decisions about how to serve and support clients. It can also make it easier to personalize customer experiences.
• Improve decision-making: Conversational analytics offer companies a behind-the-scenes look at what’s actually moving the needle for their customer satisfaction rates. Traditionally, contact centers would need to listen to countless recordings of customer conversations to pick up trends. Now, they can use AI to spot patterns, opportunities, and challenges instantly.
• Monitor agent performance: The right conversational analytics platform can give supervisors and managers a comprehensive view of their team’s performance, helping them to understand which staff members need more support. Recordings can be used to train future employees, and real-time analysis can be combined with bots to give agents advice on how to manage a situation in real-time.
• Reduce customer churn: Through conversational analytics, companies can pinpoint the exact moment when customers decide to churn, or give up on a purchase. This makes it easier to understand the pain points which might be causing missed opportunities in the business environment, and could lead to increased sales and revenue.
• Uncover Service and product improvements: Analytical tools with conversational abilities can pick up on feedback shared by a customer throughout an interaction. This can allow the system to highlight potential areas where companies might be able to make improvements to a service or product, without the need for client surveys.
• Enhance productivity: Conversational analytics can even streamline how the contact center environment operates. Using intelligent routing tools and assistants, companies can directly connect their customers to the agents most likely to have the answers they need to their questions and concerns. This leads to fewer transfers, and better business outcomes.

Conversational Analytics: The Future of CX?

As customer expectations continue to evolve, businesses are under more pressure than ever to deliver meaningful interactions at every available touchpoint. The only way to respond to customer requirements quickly and effectively, is with access to the right insights.

Conversational analytics allow companies to leverage the benefits of being able to truly listen to their customers. By diving into the deeper data hidden in conversations, brands can make better decisions about how to serve clients, create products, and even train their team members. Its little wonder conversational analytics are rapidly making their way into every facet of the CX space.