Man on green screen with pop up of conversational analytics tool

Conversational Analytics Explained: Definition and Benefits

Yasmeily Toledo PerdomoLast updated on April 29, 2024
7 min

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Knowing what clicks with customers is the key to forging long-lasting relationships and keeping them satisfied in every interaction with your company. Tracking customer conversations and gaining insights from them is the only way to boost customer satisfaction. With the help of a conversation analytics software, small and medium businesses can achieve that goal easily. 

This software can improve your teams’ productivity by reducing their pre and post-call admin tasks. By adopting this technology, your sales agents can save a lot of time spent on reviewing calls and other data. Let’s find out how your business can take advantage of conversational analytics.

What Is Conversation Analytics?

Simply put, conversation analytics analyzes customer conversations to gain actionable insights. To process and analyze unstructured conversations, AI (Artificial Intelligence), ML (Machine Learning), and NLP (Natural Language Processing) are used. 

Conversational analysis is the best way for a business to collect customer feedback that offers details into their experience with the brand, intent, actions, behavior, and emotions. The goal is to use the customer data gathered to deliver a better experience and offer personalized solutions. 

In short, conversation analytics software can understand trends and opportunities based on chat transcripts, voice or video call transcripts, or any other form of customer interaction data. 

How Does Conversation Analytics Work?

Conversation Analytics use a multistep process to extract  insights from conversations. analyzing data to uncover patterns, trends, and sentiments. Let’s take a look:

1. Key Components Of Conversation Analytics

Before discussing the process in detail, it is important to understand the key components or technologies involved in the process:  

2. NLP: Natural language processing (NLP)

A branch of AI, NLP helps conversation analytics softwares to understand and process human language. The technology is used to place voice inputs into context and extract meaning. 

3. Sentiment Analysis 

A conversational analytics tool doesn’t just interpret words and phrases, it also determines the sentiment or tone embedded within the conversation. The sentiment analysis feature helps customer support agents assess customer satisfaction and understand potential issues. 

4. Intent Recognition

This is about understanding the goal behind a customer’s call. Using this feature an agent can determine if the call is regarding a grievance or general feedback and then provide a relevant response which saves time and effort.

5. Customer Journey Analysis

The software accesses and analyzes data from multiple customer touchpoints such as chats, emails, and phone calls and then gathers insights into their journey helping customer support agents offer better solutions at the right time.

6. Performance Monitoring

The software can do much more than analyzing conversations and offering actionable insights. It can also track performance and measure KPIs like resolution rate, response time, etc. helping businesses identify areas for improvement. 

7. Personalization and Recommendations

Offering personalized solutions and recommendations is the best way to win over a customer and a conversational analytics tool can help you do that by offering you insights into the customer’s behavior and preferences.

Conversational Analytics – An Overview Of The Process 

The process starts with the collection of conversational data. AI, ML, NLP, and other sophisticated algorithms are used to transcribe the conversations, understand the context, and extract data that gives actionable insights. Let’s go into the details:

Collection Of Customer Conversation Data

The process starts by collecting data from multiple sources such as transcripts of calls, chats, emails, social media messages, and voice assistant interactions. 

The next step is to clean and standardize the data, which involves removing background noises or any such irrelevant information. This step also involves splitting texts into words and phrases, lowercasing, and removing common or stop words like and, the, etc. 


Once the data is collected and standardized, the NLP technology is deployed to understand the meaning of the conversation. The NLP algorithm analyzes the data and deciphers sentiments, intents, and context of the conversations.

Generating Insights  

Once the conversational data is processed, algorithms are used to generate actionable insights from it. The report will tell businesses more about customer preferences, sentiments, common issues they face, and the current market trends.

The information is presented using visualizing tools, helping agents easily interpret and act on the insights. As the system gets more data, it can update the models and provide them with accurate and personalized responses over time.   

From Data To Decision: Real-World Applications Of Conversational Analytics

All data and insights gained from conversation analytics software have real-world applications, empowering small and medium businesses to make informed decisions. We have listed a few of them below: 

Driving Product Innovation

Product innovation is the key to business success. By gaining insights from real time customer feedback and market trend identification, businesses can understand what their customers are looking for and drive product innovation to stay ahead of the competition. 

Optimizing Customer Service

According to a study, companies focused on customer satisfaction are 60% more profitable, and conversational analytics plays a major role in offering customers timely and personalized support.

By analyzing customer conversations gathered from multiple channels, conversation analytics software can offer you the intelligence you need to identify customer pain points and improve the performance of your support agent.  

The software can also equip your customer support agents to anticipate problems and stop them from ever arising. Chatbots, for example, can offer immediate support, reducing wait times and saving costs.

Boosting Productivity 

Conversational analytics can be used to flag certain keywords and identify problem areas. This data can be used for creating an effective routing strategy. For instance, when monitoring agent performances, managers realize that certain customer support agents are good at handling certain topics. 

This means they get to attend to issues that match their skill sets, which results in improved productivity and better customer satisfaction. 

Improving Conversions

You can tailor your sales strategies using the insights gained from conversational analytics. By using the software to analyze customer interactions, your sales team can identify patterns and optimize sales conversions. With the use of smart conversation analytics software, you can automate follow-ups and offer personalized recommendations. 

Monitoring Agent Performance In Real Time 

This is a powerful application of conversational analytics in day-to-day business. Being able to monitor and help an agent in real-time is an effective way for your business to offer on-time resolution and an improved experience to the customer. The agent can also learn how to approach a problem in specific scenarios.

Spotlight On Industries: Examples

Many industries take advantage of the benefits of conversational analytics to drive more sales and deliver better customer experience. Let’s see how some industries are leveraging the power of conversation analytics software:

Education and Learning 

The education segment harnesses the power of conversational analytics to personalize the learning experience. Chatbots are used for virtual tutoring, especially for answering questions, helping students understand difficult lectures, speeches, and concepts, and providing feedback. 

By automating grading, the software helps free teacher’s time and focus on mentoring and supporting students. The benefits also include: 

  • Multilingual support that helps non-native speakers 

  • Round-the-clock for support and guidance

  • Create a collaborative learning environment 

Health Care

Conversation analytics software can be used to diagnose health conditions online by asking a few questions to the patient. The software can help patients schedule appointments and complete their paperwork to streamline the medical process. 

The software can even be of assistance to therapists in taking notes and summarizing a session. Pharmaceutical companies can use the software to collect customer feedback using focus group surveys. 

Finance and Banking

Banking and financial services have been using conversational analytics to cut operating costs, automate functions, and improve customer experience. In the banking sector, the software can be deployed to check balances, process transactions and identify fraudulent activities by detecting certain keywords and phrases. 

In the financial sector, conversation analytics software can come in handy while resolving customer queries saving agents’ time. 

Sales and Customer Support 

With the help of conversation analytics software, sales and customer support focused businesses can understand customer sentiments, and trends, and use the insights to devise a better sales strategy and enhance customer satisfaction.

The technology can also be used in voice and SMS sales outreach to increase opportunities.  The software can track phrases your customers use, to get better ideas, or use better sales wording to spike interest.

What’s the aim of implementing conversational analytics?

Conversational analytics is one of the most exciting forms of AI. If you ever decide to integrate the software into your business here are a few best practices to follow: 


Seamless integration and scalability are the two most important factors to keep in mind while trying to implement the technology in your organization. The software should seamlessly work with your existing CRMs or any such marketing tools. You should also be able to add features as and when your requirement arises.  

Extracting Value

Gaining customer insights that can take your business to new heights is the most important feature of conversation analytics software. The technology should have an easy-to-use interface and intuitive functions and should be able to trigger important actions and measure agent performance by automatically tracking conversations.  

Compliance and Security

Conversational analytics technology can automatically record, track, and analyze all the calls leading to better data security and compliance from agents. Data is safely stored and is GDPR compliant if processes are followed correctly.

Harness the power of Conversational Analytics today. If you are ready to embrace conversational analytics, Aircall can help you with advanced conversation analytics tools that ensure compliance while bringing you actionable insights that can improve your productivity.  

Published on April 29, 2024.

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