8 Conversational Analytics Use Cases You Didn’t Know Were Possible – CX Today

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Contact centers are dependent on access to the right data, to ensure they can consistently deliver incredible experiences to customers. Now more than ever, agents need insights to help them adapt rapidly to changing customer expectations and preferences.  


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Conversational analytics tools have emerged as a critical resource for extracting valuable insights from every interaction. In fact, the market for conversational AI is currently growing at a CAGR of 21.5%, thanks to the incredible value this technology can offer.  

However, many companies still don’t understand the full potential of these tools. Here’s your insight into some of the amazing use cases you can explore with the right analytical tools.

1. Automating Quality Assurance

Quality assurance is essential in any contact center, offering a comprehensive insight into the performance of your employees, and customer satisfaction. However, a comprehensive QA strategy can be time-consuming and complex to implement with many teams only monitoring 2-3% of the total interactions.  

Conversational analytics tools can speed up and automate quality assurance strategies, using artificial intelligence to score every interaction with pre-defined criteria. That means you get a more consistent, accurate, and holistic view of QA metrics, and you save crucial time on analysis – which can be better spent on coaching your agents.  

“This really is a game-changer for QA. While we wouldn’t recommend going ‘full AI’ – you still need your QA team’s expertise to dive into those must-monitor interactions – the ability to get the whole picture from 100% of your interactions is undeniably powerful. Your QA team’s time can be put to better use, focusing in on those conversations that the AI flags as potentially high-risk and validating the results of the GenAI.”  – Matt Jones, Product Manager at evaluagent.

2. Measuring Sentiment

Today’s conversational analytics tools don’t just monitor the words said in a conversation. With advanced AI algorithms, they can examine the tone of each discussion, offering insights into both employee and customer sentiment.  

With a clear view of customer sentiment, companies can determine which actions lead to happy or unhappy customers, and build training resources for their teams accordingly. What’s more, they can maintain a holistic view of employee engagement, and potentially reduce talent turnover rates. 

3. Monitoring First Contact Resolution

With powerful AI algorithms, and the ability to process huge amounts of conversational data, the right analytical tools can help you to track critical metrics and drivers of cost such as FCR.  

You can use these tools to gain rapid insights into how often agents resolve customer queries during the first conversation, and even allow employees to monitor their own first contact resolution rates. The data you gather could even help you develop training strategies that help employees address issues at the first time of asking and reduce costs..

4. Spotting Broken Contact Center Processes

Conversational analytics tools don’t just help you to discover where your contact center is excelling. They can also offer a behind-the-scenes look at the processes you need to correct or improve.  

With automated QA tools, you can discover bottlenecks and issues within your processes, ensuring you can optimize business outcomes over time. You might even discover ways you can reduce contact center costs, by eliminating problematic processes and self-service failures that lead to complaints or customer churn. 

Nowadays, software platforms can give you instant insights into specific problem areas – whether it’s refunds, complaints, returns, renewals – you name it. These reports have the potential to go beyond the contact center and create a positive outcome for the business as a whole.

5. Predicting Customer Behavior

As customer expectations continue to evolve at an incredible pace, contact center leaders need to find a way to stay ahead of trends, preferences, and market dynamics.  

Conversational analytics tools can search for trends and patterns in historical conversations, and use those insights to predict the future behavior of customers. They can help contact centers prepare for peaks in demand, understand the changing communication preferences of customers, and even predict what customers would rate you in an NPS survey.

6. Democratizing Customer Insight

One of the biggest benefits of conversational analytics is the ability to ensure everyone in your team can access crucial customer insights in a way that they understand.  

Many platforms can simplify the process of visualizing customer experience trends, helping business leaders determine how to distribute resources effectively. They can also contribute to the feedback loop between QA and agents, ensuring everyone has access to insights on customer sentiment and intent, boosting their ability to deliver an exceptional experience in their next interaction. 

7. Enhancing Compliance

AI-powered conversational analytics tools are extremely effective at helping companies adhere to changing compliance standards. They can pinpoint sensitive topics in a conversation instantly, and help business leaders to track how well agents adhere to specific processes and specific conversations for auditing purposes.  

Plus, innovative solutions can send automated messages to supervisors when they detect potential risks so they can excute service recovery workflows and 2nd line defense strategies.  

“With regulators tightening up requirements, we see a lot of our customers really zeroing in on compliance capabilities. It’s really important to them to be able to easily find high-risk customer conversations, as well as adequately demonstrating how they’ve responded to any non-compliances. Now, it’s easier than ever to surface these insights – and regulators know that businesses can’t plead ignorance!”
Matt Jones, Product Manager at evaluagent

8. Informing Agent Schedules

Conversational analytics can even help companies make the most of their resources, assisting with the development of optimized agent schedules. They can track the reasons customers are calling your contact center (for example, chasing progress,  or updating details), ensuring you can forecast not just your overall contact volumes, but also the types of calls or conversations your agents are dealing with.  

This makes it easier to determine which team members you need at any given time, and what resources they need to deliver an excellent experience. 

Discover the Power of Conversational Analytics 

Conversational analytics tools can offer companies far more than just an opportunity to transcribe and analyze conversations. With the right AI-powered solutions businesses can transform their operations, improve resource allocation and reduce costs.  

With conversational analytics tools, contact centers can gain the in-depth insights they need to make intelligent decisions that optimize and enhance their customer experience strategy. Don’t underestimate the potential of conversational analytics for your contact center.  

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