Conversation Intelligence versus Conversational AI

There’s a Conversation Intelligence solution that improves productivity, reduces negotiation cycles and increases revenue predictability with information that can be processed directly from customer interactions.

What is it used for and in what areas is it being applied?

With the arrival of new technologies and ways of communicating, customer expectations have changed. According to reports by Gartner and McKinsey, today’s Business to Business (B2B) customers have very little time to interact with Account Managers (AMs), or Sales Representatives, devoting only 17% of their time to meeting with potential suppliers. This drops to 5 or 6% when we consider several providers, so AMs should try to make their time with customers worthwhile.

B2B buyers are also changing the way they interact with AMs, as two out of three prefer remote human interactions or digital self-services.

On the other hand, they need feedback from their managers to know exactly how they can improve. Considering that sales leaders devote only 14% of their time to coaching, a question arises: how can managers help create more opportunities for development?

The characteristics of a good salesperson (charisma, honesty, confidence, and balance) are timeless. However, considering customers’ ever-changing expectations, new ways for connecting, and innovative products showing up daily, AMs need every opportunity to improve their skills and create better shopping experiences, as Enrique Plaza points out in Zoom’s blog (zoom.us), which I will use to elaborate and explain the solution we will talk about later.

In response to these huge changes, 88% of sales managers have already invested or consider investing in intelligent analysis tools and technologies. Although there are many different commercial AI solutions, only one provides information from the source that matters the most: conversations with customers (Data First Party or data provided by the customer themselves). However, before we elaborate any further on conversational intelligence, it’s important to explain its difference from what we understand as Conversational Artificial Intelligence (Conversational AI).

Conversational AI

Conversational AI is a technology that allows machines to interact with humans through natural language processing. It consists of programming computers to understand and respond to spoken or written language in a way that simulates human conversation.

Conversational AI is used in various applications, such as chatbots, virtual assistants and voice-enabled devices like smart speakers. Its purpose is to allow humans to communicate with technology more intuitively and naturally.

Product example: ChatGPT

Conversation Intelligence

Conversation intelligence is a technology that uses AI and machine learning to analyze sales conversations and find high-impact information, such as trending topics, customer engagement and more.

In short, conversation intelligence centers on analyzing and improving human-to-human communication, while conversational AI focuses on creating human-to-machine interactions that are similar to the ones used by humans. Both are important, each in their own way, and have countless real-world applications, from improving customer experience to improving productivity and efficiency.

Having this clear, we can now say that conversation intelligence is typically used in areas such as sales, marketing and customer service, to help people and organizations better understand their users and communicate with them more efficiently. This Conversational AI is present in an application called Zoom Revenue Accelerator.

Since its features are extensive and benefits inumerous, I’ll just mention it for now, with the intention of further developing the topic in our next article.

Talk to you soon!