What is Conversational AI? Business Benefits and Application Examples

Konstantin Sadekov
November 29th, 2021

woman talking to conversational ai

In this rapidly evolving world of technological innovation, Conversational AI applications and systems are quickly becoming the preferred solution for optimized customer engagement. For a high-quality conversation to occur between a human and a machine, the computer-generated responses must be intelligent, quick, and natural-sounding.

The pioneering company, MindTitan, has developed an AI strategy for the Estonian government. The company also works with numerous big enterprises in the retail, telecommunications, banking, finance, and entertainment industries like Veon, Elisa, Swedbank, and GOSI. With extensive expertise in advanced Natural Language Processing and other AI-enhanced technologies, MindTitan provides businesses with exceptional automated, personalized interfaces that are simply unmatched.

In this article we are going to cover the following questions:

What is Conversational AI?

Also known as Conversational Artificial Intelligence, these technologies allow machines or applications to communicate efficiently and accurately with humans in vocabulary that is clear, concise, and easy to understand.

These capabilities eliminate the need for customers to complete tedious forms or engage in time-consuming phone conversations with customer service agents or sales representatives.

One of the most common Conversational AI examples is the often-popular chatbot. A chatbot is a program that interacts with and imitates human conversation using Artificial Intelligence or AI. Chatbots can perform a wide variety of task related to customer service, marketing, sales, and even IT support. Some services like Google Assistant and Amazon Alexa use AI to ensure that their platforms and services operate more effectively for end users.

conversational AI chatbot

In addition to chatbots, Conversational AI is also useful in voice-based applications via telephone or the Internet. For example, customers can complete transactions with automated call centers by speaking directly with a chatbot rather than the traditional human representative.

Furthermore, some AI-enhanced bots interact with customers by simply requesting that they press numbers on their smartphones in response to pre-recorded questions and comments from an automated system. This technology has been around for decades. In fact, many consumers today still remember the infamous “Press ‘one’ for English” synthesized voice messages whenever they were seeking answers to questions regarding banking transactions or the whereabouts of the local cable installer.

More Conversational AI applications and examples

Conversational AI is more than just chatbots. Many AI-enhanced applications available today are voice-based rather than text-based because speech recognition and natural language processing technologies are improving substantially with each passing year.  Because of these consistently progressing advancements in AI, there is an increased demand for automated call centers with extensive customer support features.

Customers today can easily transfer between departments by simply punching an appropriate number into their keypads or speaking that number directly into their smartphones. Consumers can also request daily status reports on their accounts provided via text message rather than being forced to wait on hold to speak in person with a customer service representative.

conversational AI examples

Another type of Conversational AI application involves preconfiguring e-commerce websites to answer customer questions quickly and automatically when typed directly into a Google search bar. Some websites even allow the consumer to search other websites or the entire Internet for answers to their questions.

Other Conversational AI examples include:

  • The “Okay, Google” voice command that activates Google Assistant on Android devices.
  • Conversational appliances like Amazon Echo’s virtual assistant activated by the “Alexa” voice command.
  • The Siri voice assistant found on Apple devices, including iPhones and iPads.
  • Virtual assistants like Cortana found on smartphones, tablets, and computers.
  • All mobile applications that require the user to type in questions about the product they are trying to purchase (not just chatbots, but any e-commerce store or website utilizing this AI feature).
  • Conversational Voice Response systems, in contrast to old legacy IVR bots, ask the customer to “Describe an issue with their own words” and get routed automatically without a single press of a button.
alexa and a boy

One of the most successful Conversational AI examples involves standard text-based messaging. Since 2016, Facebook has provided businesses with advanced analytics and other special features through its Messenger platform. These features enable customers to communicate directly with companies via text message, rather than calling an agent or even opening a new browser window.

How does Conversational AI work?

What is Conversational AI, and how do these applications and systems translate human language into something that a machine can easily understand?  At first glance, the process seems deceptively simple.  A customer engages with a virtual assistant or chatbot—which promptly provides an appropriate response.

However, when we dig deeper, there are several different technologies working together behind the scenes to make this virtual dialogue possible. Some of the individual components of successful Conversational AI implementation involve the following technologies:

  • Natural Language Processing (NLP) engines that comprehend complex language structures and grammatical rules—while also making direct associations between specific words and phrases.
  • Natural Language Understanding (NLU) engines that understand precisely what is being said in a text message and convert it into a machine-comprehensible format for processing by other applications.
  • Text-to-Speech (TTS) systems that take Conversational AI applications one step further by converting written text into synthesized speech for interaction with the user.
  • Advanced Speech Recognition (ASR) systems that convert spoken words into text with up to 99% accuracy.

Let’s take the simple example of a customer asking a company chatbot about its hours of operation. The customer’s speech travels through the NLP technology which cleans up and deciphers the customer’s language to determine precisely what she is saying.  In text-based interactions, NLP technologies can correct grammatical and spelling errors, identify synonyms, and break down the texted request into programming code that is easier to understand by the virtual agent.

conversational ai explained

Once the NLP technology successfully translates the original message, NLU technologies take over and clarify the customer’s primary intent behind the question. NLU technologies can also conduct sentiment analysis— useful in identifying any emotional triggers of frustration or anger from the customer’s voice.

Now that the system adequately understands the customer’s question, the Conversational AI solution needs to formulate a proper response by comparing the information acquired thru NLU with the company database of potential, pre-formulated solution flows. Then, the system quickly submits the proper response to the customer.

solution flow

Depending on the Conversational AI application, these pre-formulated responses can take the form of text or virtualized speech.  For sight- or hearing-impaired customers who prefer voice-based applications, TTS technologies can convert the pre-typed, pre-formulated text responses into computer-generated audio.  For the physically challenged, ASR technologies allow the customers to ask questions verbally rather than through manual typing.  As Conversational AI technologies continue to advance, the possibilities appear simply unlimited.

What are the benefits of Conversational AI?

It is often very challenging for businesses to provide personalized support to large groups of people simultaneously. Conversational Artificial Intelligence aims to resolve these issues by providing customers with a natural and effective mode of interaction.

With the aid of Conversational AI, customers can receive prompt and accurate information 24/7 without waiting for an available customer service representative. Many companies provide users with access to automated messaging via phone or email through a personalized interface relevant to the user’s inquiry.

Furthermore, live chat with a human agent is not necessarily the most efficient method of answering a customer inquiry quickly. Many of the most advanced Conversational AI applications involve customized systems enhanced with Machine Learning (ML) technologies that gather essential data about each individual shopper, such as their preferred product preferences.

ML technologies can also help companies identify the typical purchasing habits of individual consumers. For example, ML can help sales and marketing teams identify the number of times a customer usually visits their website before buying a product or service.

Other benefits of Conversational AI technology include:

operational cost graph

Reduce operational costs with Conversational AI applications

Conversational AI will improve customer satisfaction rates and enhance company productivity while simultaneously lowering operational costs.  With fewer employees requiring training and oversight, businesses can achieve higher ROI in a shorter period.

Conversational AI can automate both calls and chats. Overall it can handle almost 80% of the customer service making it a great investment.

Suitable for businesses involved with multiple industries

Conversational AI is beneficial to any company looking to improve customer service dramatically while avoiding massive financial investments and the constant need to train and retrain new and current staff members.

From U.S. healthcare providers that need HIPAA-compliant systems to the e-commerce merchant in Paris who requires more robust scalability, Conversational Artificial Intelligence solutions are suitable for many different types of businesses across various industries.

customer decision making process

Gain insights into the customer’s decision-making processes

By taking advantage of modern Conversational Artificial Intelligence technologies, businesses can track consumers’ online shopping habits and better understand why certain products and services are more popular than others.

Marketing teams can determine how many products a typical customer reviews before making a final purchase.

They can also identify the length of time that a customer spends reading each product’s webpage. The chatbots and other applications can then use these insights to provide more appropriate answers to customer inquiries. Thanks to ML technology, businesses now have access to invaluable feedback that would otherwise only be available by speaking directly with a human representative.

self service

Bolster self-service functionality

Self-service functions, like auto-pay for bills and other services, are becoming increasingly popular among customers who may or may not wish to interact with live customer service agents.

Conversational AI can also help companies streamline internal sales processes by providing automatic updates to product catalogs, marketing materials, and promotional content. Customers can even use chatbots configured to help them complete specific tasks, such as online purchases via the company’s website or mobile app.

return on investment

Higher Return on Investment (ROI)

Developers can custom design Conversational AI applications to provide companies with multi-channel capabilities that go far beyond conventional chat or email services, too.

For example, many AI-enhanced systems are capable of processing data from social media sites, such as Facebook and Twitter, when responding to customer inquiries. As these applications become more prevalent across multiple channels, the organization experiences a significant boost in its ROI.

data leaks

Reduce risks of data leaks

One of the most cited concerns about AI and ML technologies is that too much reliance on automated systems could lead to data leaks through malicious hacking incidents or incorrect handling of potentially sensitive personal information.

Conversational AI systems are designed to avoid potential security risks because the information they process is not typically categorized as critical.

Sentiment analysis strategies

Conversational AI will also help companies identify emotional triggers that are causing their consumer base undue stress or frustration, which may negatively impact the business’s bottom line.

Automating sentiment analysis eliminates the need for customer service agents to manually sift through thousands of social media posts, saving the company even more time and money.

scalability icon

Optimized scalability and reliability

The scalability and reliability of Conversational AI helps businesses attain higher fulfillment rates that boost their long-term ROI.

This capability is crucial for large enterprises that want to provide consistently high levels of customer support without experiencing downtime during peak business hours when customer traffic tends to spike. 

instant return

Return customer service calls instantly

Instead of tracking down an available customer service agent while placing the angry or concerned customer on hold, businesses can configure their AI-powered chatbots to instantly return phone calls instead—which saves time, money, and frustration for everyone involved.

In some cases, the contacts should not be automated, as humans will handle them more efficiently. AI can prioritize such contacts so that angry people wouldn’t be waiting on the phone line.

‘Human Factor’ and Sales Opportunities

Modern Conversational AI systems can be specially designed to learn from customer interactions, allowing companies to improve their customer relationships, consumer satisfaction levels, and even their Yelp ratings.

Conversational AI can detect sales opportunities and prioritize them. This is especially important as some portion of the calls is dropped due to long waiting times.

Enhance Brand Loyalty

Modern Conversational Artificial Intelligence technologies allow businesses to make the most of their existing resources by using automated voice or textualized chat features instead of phone calls or emails to communicate with customers and potential clients.

Direct engagement with these systems provides a more personalized experience for consumers who want customer support, too. Thanks to its ability to learn from specific customer interactions, Conversational AI helps companies improve their brand loyalty rates while boosting operational efficiencies.

 

Conclusion

conversational ai

Conversational AI applications and systems enhance customer loyalty by providing a smooth and convenient customer service experience. By using AI to respond to consumer requests, companies optimize their existing resources by boosting operational efficiency and reliability while improving ROI.

Furthermore, Conversational Artificial Intelligence creates less work for employees—which enhances compliance efforts within regulated industries, such as healthcare providers and financial institutions.

Meanwhile, modern Conversational AI will collect and process data from social media sites while simultaneously identifying emotional triggers that may negatively impact the business’s bottom line.

These capabilities alone make AI-enhanced applications an invaluable tool for today’s most competitive organizations with a primary goal of providing the best possible customer purchasing experience.

Of course, Conversational AI is not a one-size-fits-all solution for every problem related to customer service—at least, not yet.  Since supervised ML is such an essential component driving the advancement of AI-enhanced technology, developers first must perfect the process of teaching these machines to understand the specific context of text-based or voice-based customer communications.

Once the AI industry perfects this “learning” process, they must then perfect the processes of “teaching” the machines how to respond to specific questions using the solution flows.

Otherwise, a company may end up with a self-learning chatbot that morphs into something quite undesirable, as Microsoft quickly discovered just a few years ago.

In 2016, Microsoft launched a chatbot that would “learn” by dialoguing with people on Twitter. Within less than 24 hours, the new chatbot named “TayTweets (@TayandYou)” began spewing racist, feminist-hating, Nazi-loving rhetoric at alarming rates. Microsoft learned a valuable lesson: As in life, the importance of choosing one’s teachers and educational information wisely—even with AI—is crucial.

microsoft chatbot fail

MindTitan develops, deploys, and maintains custom AI products and ML solutions for a wide variety of clients from Japan to Saudi Arabia— regardless of the company’s size, industry, or business sector. We are Europe’s fastest-growing specialist in Conversational AI technologies, including call automation, chat automation, and Turnkey AI solutions for both public and private sectors.

MindTitan develops, deploys, and maintains custom AI products and ML solutions for a wide variety of clients from Japan to Saudi Arabia— regardless of the company’s size, industry, or business sector. We are Europe’s fastest-growing specialist in Conversational AI technologies, including call automation, chat automation, and Turnkey AI solutions for both public and private sectors.

Our current partnership with the Estonian government for the development of a secure and efficient AI implementation strategy and our ongoing collaboration with the EU’s largest telecommunications conglomerates makes MindTitan a trustful partner for any organization.  For more information on expert development and deployment of Conversational AI applications and systems

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