Conversational artificial intelligence (AI) uses machine learning to talk with users in a way that feels natural and personalized.
Today, we’ll explore what conversational AI is, how it works, and how you can use it in your business.
If you’re already familiar with the topic, jump to the area that’s most important to you.
- What Is Conversational AI, and How Does It Work?
- The Principles of Conversational AI
- Conversational AI and Customer Engagement
- How Businesses Can Use Conversational AI
- How to Pick the Right AI Platform/Solution
- Preparing Your Team for Conversational AI
What Is Conversational AI, and How Does It Work?
Conversational AI converges three separate technologies: artificial intelligence, messaging apps, and speech recognition.
Some of these, like voice recognition software, all have roots that stretch back to the 1990s. But combining language technology with AI has changed the game entirely.
Software that combines these features to carry on a human-like conversation might be called a “bot.” You can use the term “chatbot” for text-only bots.
If you’ve used a virtual assistant like Google Home or Amazon Alexa, then you’ve experienced a conversational AI before. They’re learning about us and we’re learning about them.
These conversational experiences are maturing thanks to deep learning. Conversational interfaces have evolved to deliver a rich and helpful user experience.
How AI Brings Conversations to Life
Conversational AI simplifies a request into its essentials to identify people, actions, objects. It does all this while interpreting the conversation as a whole.
In the example below, a caller wants to book a flight from Los Angeles to Hawaii for less than $300. It breaks down the components of the request into simpler entities for processing.
First, it records something written or said by a human. The conversation could be via a visual interface (like a mobile app) or an audio interface (like an Amazon Echo or Google Home).
Next, it interprets what the user says in a process known as Natural Language Processing, or NLP.
By using machine learning to analyze millions of human conversations, a bot can recognize that “how much does this cost?” and “what’s the price?” are asking the same question.
(A subset of NLP is Natural Language Understanding or NLU. NLU seeks to understand subtler inferences basic NLP might miss. It’s still far from perfect, and most chatbots don’t use NLU—yet.)
Based on that meaning, the bot then determines how to proceed next. In simple applications, this might be prewritten, such as providing a product’s price if the customer asks.
More complex bots will generate solutions from current and archived conversations. For example, a reboot fixed previous keyboard shortcut errors, so the bot will start to recommend rebooting.
Finally, this information—a question, response, or action—is turned into human speech. This process is called Natural Language Generation (NLG).
Sophisticated bots will generate natural language using customer service phrases they’ve learned. More basic applications might rely on prewritten scripts.
Where Can We Find Conversational AI?
These bots are all around us, from the assistants in our phones to support desk chats to automated responses on Facebook Messenger.
And they’re becoming more popular all the time.
In 2019, research showed that 40% of people who use a voice assistant like Google or Amazon Alexa started doing so in the last year.
Bots started on external devices, like computers and phones. Today, AI systems are found within wearables like watches and around us via home speakers.
As these devices become more common, so will the AI technology behind them.
The report forecasts 70% of consumers will use their voice assistants to skip visits to a store or a bank. These AI solutions will have a profound impact on e-commerce and the entire customer experience.
The Principles of Conversational AI
Ready to add conversational AI to your business? You’ll first need to decide what principles apply and how they can help you achieve your goals.
Objectives and Context
First, understand your goals behind using this type of technology. Don’t add conversational AI because it’s new. Incorporate it into a customer service strategy that offers value.
Next, look at the use cases where you’d like to add it. Conversational AI is best for simple, straightforward tasks.
Think of the three areas of context that influence whether to use AI:
- Demographic data and user interests
- History and previous interactions
- The type of activity, mood, and user intent
A bot might excel at letting a regular customer reorder their favorite products via Facebook Messenger. But a bot would almost certainly mishandle an anonymous ethics violation report via text message.
That example might sound obvious, but you need to decide where your planned implementation lies on the continuum.
Security and Privacy
Security and privacy are major concerns when it comes to bots, with almost half of users concerned about safety.
Establish norms and guidelines for the data and conversations on the application.
Conversational AI and Customer Engagement
When it comes to business applications, AI is the future of customer service, whether that’s before, during, or after a sale.
So, what makes conversational AI an excellent engagement tool?
Fluid, Personalized Conversations at Scale
In today’s environment, consumers expect an omnichannel experience—one that moves with them across devices.
A customer might start on the Facebook Messenger app, switch to Siri while driving, then complete the order on the website’s live chat.
Conversational AI can ensure personalization follows the customer across platforms for a seamless experience.
In a 2019 survey, 96% of customers agreed “it is important being able to return to and pick up a customer support conversation where it left off.” In 2018, this number was 92%.
As you design, make sure the AI user flow covers all use cases. Don’t give a user product details, for example, without a link to an order page.
Less Staff Needed During Surges
Another obvious benefit of conversational AI is automation—instead of hiring extra staff, you can rely on bots to do it for you.
In 2019, the Wall Street Journal reported that after adding conversational AI two years ago, TD Ameritrade hadn’t hired any new agents.
“Chatbots can answer basic questions about trade statuses and resetting passwords,” the article reported, “while humans help with more complex problems related to taxes and beneficiaries.”
Consumer Satisfaction Stays High
One of the primary reasons for conversational AI is to save time—it’s one of the fastest ways to improve work performance.
But while handing customer issues over to an automated system might sound like it’ll hurt the customer experience, it doesn’t need to.
A 2019 case study by Helpshift showed that despite a 20% increase in chatbot usage, customer satisfaction only declined by less than 0.2%.
And according to research published in Marketing Science in September 2019, “undisclosed chatbots are as effective as proficient workers and four times more effective than inexperienced workers in engendering customer purchases.”
(Though the same study shows that revealing the assistant is a bot early on in the conversation can reduce purchases, so be careful.)
Take your IVR to the next level with Conversational AI.
How Businesses Can Use Conversational AI
The uses for conversational AI are endless across the business cycle. Bots have a role to play in each step, from lead generation to customer support to post-purchase customer insights and analytics. As more businesses continue to adopt VoIP and other cloud-based technologies, features like AI become easier to employ.
Leads and Conversion
Surprising as it might seem, customers are more likely to trust a voice assistant than a human salesperson.
This trust gives you tremendous authority by implementing a chatbot or other type of conversational AI program.
For example, Cigniti, a software-testing company based out of Texas, sees a 40% conversion rate on their chatbot.
Customer Help and Support
So-called “help bots” are a game-changer in the world of customer support. Of companies using AI, two-thirds include it in a call center or chatbot application as an extension of CRM call center software.
And that’s what customers prefer. Response time is one of the most critical customer service metrics, and customers know it.
According to 2019 data by Helpshift, “83% of respondents would make messaging their primary means of contacting customer support if they could be guaranteed an immediate response, compared to 76% in 2018.”
The beauty of a chatbot or similar system is that it’s scalable. For industries with peak seasons, AI can pick up where staff leaves off. With conversational AI, consumers get their questions answered in real-time without waiting on a human agent.
In a study of retail in November 2018, for example, chatbots seamlessly handled a 167% increase in ticket volume without the need for temporary staff.
Using conversational AI allows you to manage one-on-one conversations at scale while handling surges—anticipated or not. It’s an unprecedented way to use personalization with more users at the same time than ever before.
How to Pick the Right Platform/Solution
If you want to get started with conversational AI, the first key is to choose the right platform.
There are many custom options available for your website or custom integration, including AI-driven chat windows and embedded interfaces.
But we’ll look at pre-built systems you can start with today. These have a few advantages—they’re faster and easier to create, and they are already on platforms people know.
For text-based bots, there are plenty to choose from—from Facebook Messenger to Twitter to Slack.
The first key is to use a platform your customers are already familiar with, and one that includes the features you need.
To find a platform your customers already use, you can look to see the channels they use to communicate with your staff now. You should also research your customer demographics and learn if there are other channels they’d like to use (or are already using without you).
Determine if you want a chatbot to automate the entire experience or just the start of the conversation with a person.
Finally, ensure the platform you use has features you need, like social media integration or top-notch security.
These extra features can use customer service psychology to create a wildly successful platform that allows social sharing and expands the app’s usage.
The Wall Street Journal demonstrates the utility of chatbots. People can simply message the newspaper on Facebook to inquire about business news and obtain updates about the market.
An innovation like this helps the media publication stay relevant even in the age of competitive ranking of the Facebook News Feed. The brand can rise above it with direct messaging to a Facebook user.
If you plan to use a voice interface, you’ll need to select a voice assistant or smart speaker platform.
As with chatbots, choose a platform your users already use. For example, an Android tech support bot would make the most sense on the Google platform.
If you’re using a smart speaker, the market leader is Amazon, with 63% of market share.
Keep in mind that smartphones and smart speakers use the same platform. So while Apple’s HomePod only makes up 4% of the smart speaker market, the iPhone makes up 45.2% of the US smartphone market.
Getting Your Team Ready for Conversational AI
Finally, you’ll need to prepare your team. While AI doesn’t need humans to keep it running, your team still needs preparation to work with AI.
Explain the Employee’s Role
When employees find out you’ll be implementing conversational AI in the business, they might fear for their jobs.
But putting off the transition to AI isn’t the answer.
Technology trends show that communication is becoming more instant and interactive. This trend is why businesses can’t dismiss conversational AI as a fad—it’s quickly becoming a customer expectation.
Instead, explain that they’ll take on new roles with the technology.
As Oracle CEO Mark Hurd said, “there will actually be more people in IT, but more people in IT working on a different set of tasks…Everyone needs a boss, including bots.”
The goal is to use conversational AI at a level that helps your employees succeed, but not so much that it replaces them.
Ensure Seamless Transitions
Most processes—especially at the beginning—will incorporate human interaction at some level. You’ll want to ensure a seamless transition between bot and human.
Typically, this involves handing off the conversation to a human for infrequent topics that have a lot of complexity or rely on empathy. It’s usually cheaper to rely on an employee’s customer service skills than to let a bot handle these situations.
Make sure you train your team in the process, and the transition is seamless for customers and prospects.
Related: What is Business Communication? Why Do You Need It?
Getting Started with Conversational AI
If you’re considering getting started with conversational AI, there’s no time like the present. As technology continues to improve, we’ll see greater and greater leaps in what we’re able to do.
The sooner you have a strategy for using conversational AI, the sooner you’ll see results. There’s a reason the most prominent companies are investing millions in this technology. When you increase customer touchpoints, the latest set of technologies serves them better.
How can you start using conversational AI in your business?
See how it dramatically lowers costs and wows customers.