What Is Conversation Intelligence?

Examining the raw content of your interactions and extracting useful key information for your business and the improvement of your customers' experience is what conversation intelligence offers. The market is booming and is expected to reach a valuation of $46.8 billion by 2033.

But how can you practically use it in your daily operations? Can conversation intelligence technologies be easily deployed? Moreover, how do these technologies work?

Let's start with a simple definition, which is always useful.

What is conversation intelligence?

To answer this question, it is important to explain that conversation intelligence is primarily about the ability to understand and analyze written conversations in order to extract important information.

In essence, we are all capable of this as humans, and conversation intelligence is not exclusive to AI. However, where AI becomes interesting is in its ability to quickly process large volumes of data automatically.

Indeed, by combining natural language processing and deep learning, it can analyze long audio or written conversations to extract key information. This data can be very useful for sales and customer service teams as it contributes to customer knowledge.

Advantages of conversation intelligence for sales teams

Imagine a world where every interaction is imbued with deep understanding and surgical precision in addressing customer needs, regardless of their stage in their journey.

Although this may seem somewhat utopian, this is precisely what conversation intelligence is moving towards. Let's explore its benefits for sales teams:

• Increased and accurate understanding of customers
• Identification of best sales techniques
• Onboarding optimization
• Identification and analysis of sales trends

Understanding customers more quickly and accurately

Sales teams can use conversation intelligence to gain a better understanding of their customers' needs.

For example, when a customer interacts with a chatbot on a company's website, or by phone with a real agent, each question asked and each response provided is recorded and then analyzed.

The algorithms then deliver valuable insights into the most common concerns of customers, on a large scale, and not just on an individual basis.

Points of friction in the purchasing process, or the most requested products, features, and services are quickly identified.

Salespeople can thus better target their efforts, adapt their sales strategies, and personalize the customer experience to effectively meet their needs, no matter how specific. Ultimately, this helps to create closer relationships and sales opportunities that are more likely to succeed.

Identification of best sales practices

Communication is at the heart of any successful transaction. Conversation intelligence acts on this point as a catalyst.

How? Simply by providing you with the data on a silver platter to refine your communication skills based on conversations that have led to a sale.

The goal is to identify the levers, tactics, and even the words that have convinced prospects to become customers.a

Onboarding optimization

Joining a new team is not always easy. The recruit often has to familiarize themselves with current processes, learn to master various tools, record and understand a large volume of information to be effective.

Conversation intelligence can alleviate this pain point by guiding recruits through recommendations throughout their learning phase, helping them become self-sufficient more quickly.

Identification and analysis of trends

This is the last advantage we wanted to emphasize. You are not unaware that anticipating trends is important to remain competitive. By analyzing customer conversational data, you can, in some cases, anticipate their behavior and thus personalize the offers you make to them. Let's take a basic and concrete example.

Suppose a fruit delivery company uses a conversational platform to interact with its prospects and customers.

Through these interactions, artificial intelligence will collect a multitude of data, such as the most popular fruits, the regions where demand is strongest, the times of year when certain varieties are preferred, etc.

The company can even spot emerging trends such as the growing interest in certain fruits over a specific period. Based on this information, it can then decide to expand its range of products to include more options regarding these fruits at a given time.

Advantages for customer service

Conversation intelligence also offers interesting advantages to customer service teams:

• Respond quickly and accurately to customer requests
• Proactivity
• Availability

Respond quickly and accurately to customer requests

Conversational AI allows customer service teams to respond quickly and accurately to customer requests through the use of intelligent chatbots. For example, imagine a customer visiting a company's website and asking a question about a specific product via the chat window.

The chatbot, equipped with conversational intelligence, is able to analyze the customer's question and provide a relevant answer instantly, based on a previously established knowledge base.

If the chatbot fails to provide a satisfactory answer, it can also direct the customer to a human agent, providing precise context on the customer's request.

Thus, conversational intelligence enables a quick and accurate response to customer requests, thereby improving their overall experience.

Proactivity

Conversational intelligence tools can act as intelligent assistants to analyze verbal and textual interactions and identify customer needs, sometimes even before they express them explicitly.

This anticipation of needs and the ability to proactively address them not only increases customer satisfaction but also optimizes team efficiency by allowing them to focus their efforts on higher value-added tasks.

Always available customer service

Conversational intelligence transforms customer service by offering the possibility to remain operational 24/7, thanks to instant automated assistance, available even outside traditional office hours.

With the help of advanced chatbots and other automated response technologies based on AI, customers have the freedom to submit their questions, report incidents, or seek support at any time. Thus, it is no longer necessary to set up a telephone hotline, which has the advantage of reducing costs.

How does conversation intelligence work?

Conversation intelligence works by using technologies such as natural language processing (NLP). Let's take a closer look at this.

NLP allows for understanding, interpreting, and generating language. NLP uses techniques such as text segmentation, morphological analysis, syntax detection, and semantics.

Language understanding is essential for effective conversation intelligence. It allows the system to detect the intention behind the words used by the user to provide precise insights or a relevant response when it comes to a conversational chatbot.

An effective conversation intelligence system is also able to detect feelings and emotions. How?

By using sentiment analysis to determine if the terms used in a conversation are mostly positive, negative, or neutral. The most advanced conversation intelligence solutions also use speech emotion recognition.

This allows determining the speakers' emotions from an audio signal using data on pitch, voice tone, or even sound intensity.

Different types of conversation intelligence tools

Conversation intelligence relies on various tools that allow for analyzing conversations between a brand and its customers. Here are the main tools:

Focus on Empower: Ringover's conversation intelligence technology

And what about data security in all this?

Like AI in general, conversation intelligence raises important questions regarding security and compliance, particularly with regard to regulatory compliance and the protection of personal data.

Conversation intelligence tools may need to process sensitive information. They must therefore comply with applicable laws and regulations, such as GDPR in Europe, to ensure the confidentiality of users.

For their part, companies that use and deploy conversational analysis solutions within their teams must ensure that personal data is collected and used ethically and transparently. They must put in place safeguards to prevent leaks or misuse of this data.

Ringover has taken the necessary measures to ensure the security of the data processed in all the solutions it develops to enable companies to improve their customer relations in full compliance with current legislation.

What to remember about conversation intelligence

Conversation intelligence offers many advantages to companies, especially to sales and customer service teams. It allows for a better understanding of customers and increased customization of interactions.

Coupled with a good strategy, conversational intelligence can lead to increased sales and customer satisfaction. Conversational intelligence tools are evolving very rapidly. They are becoming increasingly powerful, accessible, and their use offers a clear competitive advantage. Conversational intelligence is gradually becoming an indispensable set of technologies.

To learn more about how Ringover can help you adopt conversational intelligence within your organization, request a personalized demo and try a free trial of Empower now!

Conversation Intelligence FAQ

What are conversational AI tools?

• Chatbots
• Conversational analysis tools
• Generative AI tools
• CRM platforms

1. Chatbots

Chatbots are conversational agents that can interact with customers via text chat or voice. They use natural language processing (NLP) to understand customer requests and provide automated responses. Chatbots improve the customer experience and relieve teams of repetitive tasks.

2. Conversational analysis tools

Conversational analysis tools are designed to extract insights from interactions between customers and the company. They use advanced text and data analysis techniques to identify trends, customer sentiment, potential gaps in agent responses, but also positive points. These tools provide valuable information to optimise your setup and adjust sales and customer service strategies.

3. Generative AI tools

Generative AI tools are based on machine learning models to autonomously generate conversational content. Generative AI tools can create more flexible and natural responses than traditional chatbots by adapting to the nuances of human language and specific contexts. These tools are often used to enrich customer interactions by providing more personalised responses and simulating more authentic human conversations.

4. CRM platforms

CRM platforms (Customer Relationship Management) increasingly integrate conversational AI features to improve customer interaction management. They allow companies to track and manage conversations with customers across different channels, automate responses to common queries, and centralise customer data for a comprehensive overview. By combining conversational AI capabilities with traditional CRM features, these platforms offer a holistic approach to customer relationship management, thus promoting a consistent and personalised customer experience. If your CRM does not have conversational AI, you can integrate a third-party tool without having to change your entire technology stack, subject to compatibility between software.

Does conversation intelligence replace customer service agents and salespeople?

No, conversational intelligence is not intended to replace customer service agents or salespeople. In fact, it assists them by providing useful information about customers and how to improve their overall experience. Conversational intelligence allows them to focus on higher value-added tasks or on strengthening relationships with customers.

How do I implement conversation intelligence in my team?

Implementing conversational intelligence may require a certain level of AI knowledge and the help of specialists. First, discuss it with your technical team. You can then choose a conversational intelligence tool like Empower by Ringover, configure it according to your business, and train your team to use it. The solution is also very easy to use.

Whatever your choice on implementing conversation intelligence in your team, follow these steps:

1. Set your goals
2. Assess your needs
3. Choose the right tools
4. Integrate the tools into your technology stack and train your employees on their use
5. Test and iterate
6. Deploy and monitor