How Artificial Intelligence is Transforming Customer Service – 7 Use Cases

Artificial intelligence is no longer about robots and sci-fi villains or about replacing humans and taking jobs away. It took a while but people have finally understood that AI is here to stay, to make our lives easier, and to help businesses thrive, and empower them to make informed decisions based on insights and analytics about their customers.

Over the years, the role of artificial intelligence in customer service has evolved sophisticatedly. With the introduction of artificial intelligence tools like ChatGPT, AI has become an indispensable part of our digital ecosystem. Today, most organizations trust its capabilities to establish a seamless customer service journey from end to end. Backed with cutting-edge AI technology and AI tools, more and more companies are confidently focusing on customer-centric strategies and offering personalized services.

Before we assess how AI is used in customer service and redefined the norms, which have been phenomenal in all ways, let’s give you a little brief of the history of artificial intelligence in customer service.

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History of AI in Customer Service

Did you know that the very first chatbot named ELIZA was developed in the 1960s? Popularly called chatterbot, ELIZA was an early natural language processing computer program that assisted doctors diagnose a patient’s condition and treat them.

ELIZA’s creator, Joseph Weizenbaum’s vision of the chatbot was to develop the study of human-machine communication. It used pattern matching and substitution to imitate conversations, giving users the impression that the program understood what was being said, although there was no evidence that either party had actually understood the other.

An online survey by Gartner revealed that customer data and analytics were recognized as “very or extremely crucial” for accomplishing their company goals in 2023 by 84% of customer service and service support leaders.

Chatbots

The evolution of customer service has been interesting. Brands have evolved and so have the customers. Brands know their customers more than ever and customers ensure they are heard and attended to, all because of artificial intelligence.

In recent times, with the launch of OpenAI’s ChatGPT, we can’t help but think of the effortless communication brands are enjoying with their customers. Chatbots, ever since their launch (in the 60s as we mentioned earlier) have redefined how brands approach customers, offer a personalized journey, and how they handle simple as well as complex queries. Timeliness forms an integral part of customer service and chatbots are simplifying this process further.

Customers no longer have to manually dial the customer support team to resolve an issue. All they need is an internet connection to get immediate resolutions from the chatbots.

Customers can use the live chat channel to write their questions and get prompt and accurate responses from the automated agent. The bots are accessible around-the-clock, meaning customers can get assistance anytime, anywhere.

• Chatbots enable customers to find the exact answer to their queries from any device or location.
• Greet customers personally.
• 24*7 availability.
• Instant resolutions.
• Saves time and money.
• Imitates human conversations.

A survey by Gartner revealed that chatbots are set to become the primary customer service channel in the next five years. Another support survey comprising 50 respondents conducted online in January and February 2022 found that 54% of respondents reported employing a chatbot, virtual conversation assistant (VCA), or other conversational AI platform for applications involving customers.

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Augmented Messaging

Needless to say, chatbots are excellent at resolving simpler problems, but the majority aren’t equipped to handle delicate or complex, or sensitive issues or situations.

For instance, there could be times when a customer feels the bot isn’t giving the answers they are looking for and they feel exasperated with the responses and hence feel subjected to inadequate service. The main limitation with bots is that their responses are based on pre-written data, and therefore it becomes difficult to save the situation when the bot is only capable of offering assistance in general.

Here is where the role of augmented messaging and customer communication comes into play. This AI program finds situations where human agents should intervene and assist the client. The agent can either handle the case further at that point or return it to the bot. What works here is the level of personalization augmented messaging brings along, resulting in an enhanced customer experience.

We do agree bots work the best in saving time for the team as well as the end users but the shortcoming remains the golden human touch, providing customer delight. Augmented reality in customer service in a way brings together the best of both worlds and helps brands to create delightful, personalized service experiences.

Sentiment Analysis

In a futuristic perfect world, bots will be endowed with the right technology to sense the customer’s emotion behind a message and figure out if it’s going in the right direction or not. In case it’s no, they would be able to provide personalized responses depending on their assessment of the situation. This too shall become a reality soon!

In the current situation, many bots use natural language processing and sentiment analysis techniques to understand and carefully evaluate user reactions.

Consumer sentiment analysis is an automated method or tool for identifying emotions in online conversations to learn what and how customers think and feel about your good, service, or brand. It helps companies in learning more about their customers and efficiently respond to them.

And in order to prevent the bot from inflaming the client’s emotions when attempting to help them, this tool instructs the bot how to respond when a customer behaves in a specific way.

Sentiment analysis in customer service comes in handy when you are drafting emails. Certain applications, like Grammarly, have the ability to evaluate your writing and provide you with advice on how your audience might interpret your message. It employs an emoji to indicate whether your email is upbeat, kind, formal, etc.

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Email Distribution

Sentiment analysis is great for both outgoing as well as incoming messages but we cannot overstate the importance of email distribution. From reaching out to prospective clients or messaging within the teams, email is extremely critical in customer service. Did you know that globally, around 3.8 million people use email to do business?

Many organizations are implementing this AI tool to read and tag customer emails to enable their support teams to respond to messages quickly and efficiently. When there’s an incoming email, the AI reads the message to evaluate the customer’s problem, emotions, and history with your brand. Accordingly, it tags and further allocates the message to the rep who can handle the issue perfectly. This tool is especially great to save time for your brand and the customers.

While rookie agents may handle simple tickets, your most seasoned ones can manage complex problems. In instances when the case is time-sensitive, your reps will be aware that they need to find a resolution as soon as possible for the customer. It is significantly simpler for a support team to fix a problem when this case information is evident at the outset of the inquiry.

Channel Directory

An omnichannel support experience is among the essentials for the smooth functioning of customer service. The only challenge with this is that you have to keep a tab on each channel that’s used for customer service. But the good news is, AI identifies the right channel and directs customers to the particular support channel that’s best suited for their issue.

For instance, the AI can advise the consumer to call in for a faster answer if all of your chat agents are occupied processing cases. Likewise, if a consumer is typing a very long inquiry on your email form, it can offer that they call or chat in for specialized service.

Voice Analysis

One of the last channels to integrate AI features is phone assistance, and there’s a good reason for that. It’s because reading text is considerably simpler than listening to phone calls as they typically include some kind of background noises, sudden tone changes, and verbal slip-ups. These can easily confuse machine learning.

Speech data provide customer insights that are simply not available from other sources, assisting in the identification of the root causes of customer annoyance and highlighting opportunities to enhance compliance, operational effectiveness, and agent performance.

But AI is a champ in finding a way around this. They are smart and technologically wise enough to offer recommendations to your reps in real-time while they’re speaking with your customers. These recommendations are based on the current phone call as well as previously obtained data on the client.

Technology in this area will advance and become a great tool for cross-selling and upselling in the future. The bot can see exactly where the buyer currently is in the journey and accordingly assesses to see if there’s a window of opportunity to sell any additional products depending on their service needs. This reduces friction and makes it an easy handoff to your sales team.

Data Management

Not all AI features are directed toward customers. In fact, tools that are connected to your own software are some of the most helpful ones.

For instance, AI when teamed with your CRM can recall customer data for your service agents. Based on the data the AI has provided, your customer success team can use this functionality to provide clients with proactive service. The AI can identify a devoted customer who hasn’t interacted with you in a while and alert your team to get in touch. This keeps clients interested in your company and shows that you care about their long-term objectives.

Final thoughts

To sum it up, the role of artificial intelligence in customer service is revolutionary in every possible way. The way brands interact with customers and offer resolutions today has changed tremendously and is way different than what we did almost 2 decades ago. With an arsenal of artificial intelligence tools, every company can find a suitable one to support their business and improve customer experience. The bottom line is AI in customer service has surpassed the buzzword stage, it is now a mandatory tool essential for survival.  These could be in any form – machine learning data, chatbots, speech recognition, and sentimental analysis. Companies can choose from an endless variety of AI customer service use cases because AI is here to stay.