What Is Conversational AI?

Conversational artificial intelligence (AI) uses machine learning (ML), natural language processing (NLP), automatic speech recognition (ASR), and contextual awareness to simulate human conversation for customer service purposes. Conversational AI recognizes and “understands” human speech and text across multiple languages. Examples of technologies that make use of conversational AI include advanced chatbots, virtual agents, automated messaging, and voice-enabled applications.

How Conversational AI Works

To understand how conversational AI works, it’s useful to understand how a traditional chatbot works. Chatbots use logic rules and decision trees to answer questions and resolve customer issues. This works well for simple queries. But traditional chatbots can come unstuck if your customers don’t include the right keywords or if their grammar or spelling isn’t consistent with what has been scripted. So, what is the key differentiator of conversational AI?

In contrast to a traditional chatbot, conversational AI uses advanced technologies to mimic human interaction. This means it can interpret tone and intent, decipher speech and text that falls outside set parameters, and give personalized responses. Conversational AI continually improves, too, learning from previous interactions.

Types of Conversational AI

ML and NLP let conversational AI process, understand and respond to human language in a more natural, organic way.

Machine Learning

ML is a branch of AI that uses algorithms and data sets to improve operations. It identifies patterns and makes predictions based on experience. In conversational AI, ML can learn from previous customer interactions and improve its responses.

Natural Language Processing

NLP uses ML to help analyze written or spoken human language. This involves interpreting voice or text data to determine its meaning. When NLP interprets a recorded customer service call, for example, it uses automatic speech recognition (ASR) and natural language understanding (NLU) algorithms to analyze the speech.

After interpreting the data, NLP applies natural language generation (NLG) to create an appropriate, personalized response. ML algorithms then help improve response quality and ensure accuracy.

How Does Conversational AI Help Businesses?

With conversational AI, you can automate more natural, human-like interactions with customers. This benefits your business in several ways:

Improve customer service

•   Answer FAQs.
•   Offer personalized product recommendations.
•   Increase customer engagement.
•   Allow customer support agents to focus on more complex issues.
•   Operate in multiple languages.
•   Ensure consistency and comprehensiveness in responses.
•   Eliminate wait times.

Ensure constant support

•   Offer around-the-clock service across all channels.
•   Provide customers with additional information and recommendations.
•   Follow up with questions to gain more information.

Reduce operating costs

•   Lower staffing costs.
•   Reduce training requirements.
•   Provide 24/7 availability (without hiring human staff for all hours).
•   Expand offerings and geographies without needing more staff.

Maximize sales opportunities

•   Engage more quickly and frequently with customers.
•   Increase customer loyalty by boosting satisfaction and referral rates.
•   Better identify upselling and cross-selling opportunities.
•   Leverage cart information, purchase history, and prior inquiries to personalize services and recommendations.

How to Implement Conversational AI

Here’s a useful things to consider when introducing conversational AI to your business:

Select a Conversational AI platform

Choosing the right conversational AI platform is the most important step in the process. This will set the foundations for everything that follows. Be sure to consider the following:

•   Research AI, ML and NLP to determine the scope of your implementation.
•   Figure out which areas of your business could most benefit most.
•   Evaluate what is possible: Which of your internal processes can be automated with conversational AI? Can the tools you are considering do those things?
•   Conduct a software demo to assess ease of use, functionality, and appropriateness for your business goals.

Identify common customer questions

Once you have selected the conversational AI program that best meets your company’s goals, create a list of questions that are likely to come up.

Develop goals and objectives

Combine corporate goals with your list of FAQs to determine the issues you would like the conversational AI to address.

Once you have these, encode the conversational AI program with the potential language/phrasing a customer may use to ask each question. Analytics and support teams can help you identify variations to specific questions.

Use goals to identify key words

Keep your goals in mind as you identify key words that will help direct conversational AI and customer interactions. For example, a healthcare customer might use key words such as “patient ID” or “prescription.”

Create a conversation with users

Your conversational AI will combine your goals, FAQs and key words to establish its rules, analyze content and interact with your users. As it gains experience and data, conversations with customers will become increasingly relevant, natural and personalized.

What to Look for in a Conversational AI Platform

There are specific features you can look for when assessing the available options. Here are some questions you might ask about features or platform components:

•   Platform programming and vendor support. The first category to assess is the back-end of the platform—how the system is programmed and what sort of support is available from the vendor. How sophisticated is the platform’s NLP program, and how is it implemented? How accurate, relevant and natural are the given responses?
•   Platform scope. Next, evaluate what areas the conversational AI platform can cover. Can the platform operate and integrate over multiple channels? Will it present a unified experience for stakeholders while also providing relevant responses based on the user’s circumstances?
•   Ease of use. Another element to consider is how user-friendly it is for stakeholders within your organization. How easily can users monitor, review and update training data to improve the platform’s performance?
•   Interaction with customers. Finally, the interface between the conversational AI platform and your customers must be natural and seamless. Is it easy for customers to access? Are its responses clear, relevant and useful?

Common Industries that Use Conversational AI

You might wonder, what is an example of Conversation AI in use? A variety of industries use conversational AI for specific purposes:

•   Retail and e-commerce. Make product and service recommendations, track orders and inventory, and manage complaints, feedback, returns and refunds.
•   Human resources. Save time and money with automatic recruiting and query responses, perform automatic background checks, address candidate questions with personalized interaction, and assist new hires with onboarding and training.
•   Healthcare. Update and manage patient records and medical histories, field questions about community diseases, send medication reminders, schedule meetings and appointments, and automate front-office paperwork and calls.
•   Insurance. Generate qualified leads, provide personalized policy recommendations, manage policy claims and renewals, and offer customer awareness and education materials.
•   Manufacturing. Monitor supplies and inventory, automate customer support queries, provide personalized product recommendations, and send tracking and delivery updates.
•   Banking and Financial Services. Provide personalized product, service and spending recommendations, check balances and process transactions, screen and process applications, and detect and prevent fraud.

The Future of Conversational AI

Conversational AI continues to expand and find new uses. Messaging apps and social media platforms are now using it to reach more potential customers. Governmental organizations use it to distribute emergency notifications, respond to queries, and share public safety guidelines. Conversational AI is being integrated into digital assistants. It supports workers in tasks like scheduling, drafting emails, and entering and interpreting data.

About Sutherland Conversational AI

By integrating with your CRM and enterprise systems, Sutherland can design, develop, monitor and maintain an advanced AI chatbot custom-built for your business needs. Sutherland Conversational AI helps ensure consistent, satisfactory interactions for your sales, support and other enterprise processes.

An evolving service that adapts to the needs of your customer lifecycle, Sutherland’s enterprise-grade conversational AI applications can help:

•   Automate customer self-service interactions and business processes.
•   Convert website traffic and generate more qualified leads.
•   Improve customer service and user experience.
•   Expand after-hours support.

Sutherland Conversational AI features:

•   A dynamic, interactive user interface.
•   Machine Learning and Natural Language Processing technologies.
•   Customized conversational design.
•   Integration with common CRM and enterprise chat platforms.
•   Conversational analytics.
•   GDPR-certified program.

Discover More About Conversational AI From Sutherland

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