What Is Conversational Intelligence?

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Conversational intelligence offers many great benefits to organizations and individuals alike, but there are still plenty of misconceptions about what it is and how it works.

When most people hear of conversational intelligence or conversational AI, their first thought is likely to be of a smart device or a chatbot.

Chatbots are projected to save businesses and consumers up to 2.5 billion hours in wasted time by 2023 and a wide range of voice-enhanced devices capable of understanding conversational language have already penetrated the market.

However, there is much more to this technology than most are aware of. Keep reading to learn more about conversational intelligence, how it’s used, and how to optimize conversational intelligence to achieve your business goals.

Definition of Conversational Intelligence

Conversational intelligence is a combination of machine learning and natural language processing technology.

Instead of relying on surface-level assessments of written or spoken information, conversational intelligence leverages the adaptive powers of artificial intelligence (AI) to spontaneously deduce intent, sentiment and meaning from such data.

This makes it possible for teams to assess large numbers of interactions much more deeply and in a relatively short amount of time.

Conversational intelligence can be used in many ways (more on this below), but what makes it valuable to organizations is the depth of insight it delivers into individual interactions between customers and service reps.

This branch of AI tech helps answer important questions about customers’ needs, while reducing the overall workload of agents at the same time. This is accomplished by using machine learning techniques to power the following pair of natural language processing steps:

  1. Input Analysis: In this step, text or speech converted to text is analyzed to determine the meaning or intention behind it. This may involve the use of a number of complex processes such as lexical semantics analysis (parsing word meanings in context), name recognition, relationship extraction, etc.
  2. Response Generation: Here, a conversational intelligence system crafts a fitting response to the input it has assessed. It is important that this be handled quickly for the response to be useful. Machine learning kicks in to help refine the above steps over time, producing increasingly accurate assessments and far more useful responses as it develops.

How Conversational Intelligence Is Used

Conversational intelligence can be utilized as a load balancing, agent-routing solution, a real-time coaching assistant and more. Here are a few key uses cases for conversational intelligence:

Streamlining Customer Support

Conversational intelligence helps improve customer service processes in a variety of ways. By leveraging this technology, customer service reps can trim the amount of time it takes to resolve customer issues and inquiries and improve customer satisfaction.

Research can be completed and potential answers to common questions can either be provided for agents to choose from or presented to customers directly, freeing up time for more demanding tasks.

Conversational AI is also capable of automatically directing incoming customer concerns to appropriate team members, preventing unnecessary transfers before a human conversation begins.

Simplifying Coaching and Onboarding

New recruits at any company need careful instruction and oversight to hone their skills in their positions. Conversational intelligence makes providing these much easier for organizations with high turnover and challenging workloads.

By answering questions and guiding agents’ actions in a call centre environment, for example, conversational intelligence can support the coaching process new hires depend on to develop.

This technology can also be applied to call monitoring efforts, signaling to managers when a customer interaction may need expert intervention to be resolved correctly.

Powering Voice Controlled Electronics

Voice-responsive consumer smart devices and enterprise-grade electronics alike have come into focus as powerful assistive tools with far-reaching capabilities.

From making devices more accessible for those who rely on assistive technologies to powering security measures that are based on voice biometrics, conversational intelligence has many applications.

Tips to Optimize Conversational Intelligence

Getting the most out conversational intelligence comes down to understanding what the technology excels at and what its limitations are. Here are a few tips that can help you optimize it for the use cases you may have in mind:

  1. Before you attempt to incorporate conversational intelligence into your organization or workflow, determine who will be using it and why. By defining your audience ahead of time, you can keep any new implementation of this technology aligned with your objectives.
  2. Avoid forcing users to interact with AI. Allow conversational AI to enrich the customer journey without becoming an impediment by providing an easily accessible alternative or “exit.”
  3. Do not ignore the data conversational intelligence tools collect. As individuals interact with your system, capture their interactions for deeper analysis, trend-spotting and business performance improvement.

Conversational intelligence is a powerful tool that can help organizations gain a deeper understanding of customer interactions, such as insights into customer intent, sentiment, and other valuable data.

It’s already being used in a variety of ways to impact call centre performance, and it’s likely that further innovation will increase the potential of conversational intelligence as a technology that drive business improvement enterprise wide.

How does your business leverage conversational intelligence?

This blog post has been re-published by kind permission of CallMiner – View the Original Article

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About CallMiner

CallMiner CallMiner is the leading cloud-based customer interaction analytics solution for extracting business intelligence and improving agent performance across all contact channels.

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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: CallMiner

Published On: 8th Jul 2021 - Last modified: 13th Jul 2021
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