7 Examples Of AI In Customer Service

Organizations are turning to AI to bridge the gap as demand for improved and personalized customer experiences grows.

Advances in artificial intelligence continue to pave the way for greater efficiency throughout the organization, especially in customer service. Chatbots are still at the forefront of these changes. Still, other technologies, such as machine learning and interactive voice response systems, are creating a new paradigm of what clients and customer service agents may expect.

Types of artificial intelligence in customer service

Artificial intelligence (AI) is intelligence created and displayed by machines and computers rather than the human brain. AI comes in all shapes and sizes.

There are usually two types of AI: narrow AI and general AI. Narrow AI is what we see in computers and smartphones daily. These intelligent systems perform specific tasks without the need to do programming.

Examples of narrow AI are speech and voice recognition systems such as Siri or Alexa, vision recognition systems in self-driving cars, medical AI scanning MRI results, and so on. On the other hand, general AI is what we see more often in movies, the type of AI that learns itself to do any task humans can do.

Narrow AI has broader applications in customer service. It supports clients by guiding them and answering any questions or requests along the way. In addition, it manifests in customer support chatbots, customer self-service, machine learning for client data analysis, natural language processing for voice recognition and support, and many other essential use cases.

How to use AI in customer service?

AI is an excellent tool that provides exceptional customer service. Chatbots perform various actions, from reminding shoppers to return to their shopping cart to collecting reviews and asking them to write a review. AI in customer service means being available 24/7 around the world in any language, inevitably attracting new clients and increasing their satisfaction.

The AI also work hand-in-hand with support agents, replacing them with basic tasks and allowing them to focus on more complicated cases. AI-based solutions such as chatbots easily recognize voice triggers and provide relevant information and recommendations without human intervention.

Another way to introduce AI into customer service is through data collection and analysis. The amount of information generated by customer communications is vast and provides valuable insight into client behavior, preferences, churn rates, and more.

With AI, you don’t have to analyze and draw conclusions from the data manually. AI also helps provide comprehensive insight into customer, interaction and conversational analytics.

The impact of artificial intelligence on customer service

AI solutions can make a lot for customer service. These powerful tools help with almost any day-to-day task a help desk agent performs. Here are some ways AI helps to interact with clients:

• Capturing leads quickly: the convenience of AI has spawned a new industry where companies now answer questions almost instantly. The growth of competition and alternatives makes it less likely clients will choose you if you do not meet their expectations.
• Quick resolution of requests by channels: companies need to strengthen their presence in these channels for brand building and marketing. It requires handling inquiries from customers received through instant messaging apps or social media channels while staying true to your company’s tone of voice.
• Efficient support service 24 hours a day, seven days per week: customers’ attitudes towards your company will change dramatically depending on how you communicate. Your users expect smooth and fast conversational AI responses that define their overall business experience.
• Personalized support services: the more personalized client support, the better! Chatbots and voice bots powered by conversational AI help you provide a customized experience for each end user.
• Reduced customer service costs: previously, human resources were used to solve complex cases. However, this approach is costly and time-consuming as it requires hiring an additional team of employees or investing in new software, which can also be expensive. Fortunately, artificial intelligence is a cost-effective way for companies, large and small.

Clients expect exceptional treatment and outstanding experiences, a need that artificial intelligence satisfies. It reduces waiting times, responds to all inquiries and questions in real-time, recommends related products, and handles complaints.

How to set up AI to work in customer service?

The excellent news is that many AI solutions, such as chatbots, can quickly be added to your website. It may seem unbelievable, but you must only follow a few steps to set up AI in your customer service.

• First, you need to identify the primary goal of your AI solution. Will he answer questions from your customers using a chatbot? Analyze data with machine learning or NLP?
• Next, you need to select the main channels. As we speak about chatbots, there is a whole range of options: a website, social networks, instant messengers, mobile applications, and much more. Choose the specific tool that suits your needs.
• Finally, tailor your solution to your needs. Teach it, test it, and see if it’s right for your company.

Setting up AI for support pays off. It improves lead generation, streamlines workflows, provides excellent client experience, saves costs, and prevents burnout, among other things.

Some examples of using AI in customer service

AI is mainly associated with chatbots in the customer service industry. Undoubtedly, chatbots make up a significant part of the market as they offer a variety of support. However, there is always something to discuss regarding AI in customer service. Below we have described 7 examples of the future of AI in the customer service industry:

1. Chatbots: one of the most popular uses of AI in customer service is chatbots. Businesses are already using chatbots of varying complexity to resolve routine issues such as delivery dates, debt, order status, or anything else received from internal systems. The customer service team helps more people and improves service quality by passing these frequently asked questions to the chatbot.
2. Agent assistance: in many of today’s multi-channel contact centers, agent assistance technology uses artificial intelligence to automatically interpret what a client is asking, search for knowledge base articles, and display them on the screen of a help desk agent during a call.
3. Self-service: clients can identify and find the support they need without relying on a customer service agent. If given the opportunity, most clients would prefer to solve problems independently if given the proper tools and information.
4. Robotic process automation (RPA): it automates many simple tasks that an agent used to perform. Automating bots to update records, manage incidents, or provide proactive customer interactions significantly reduce costs and increase efficiency and turnaround time.
5. Machine learning: it is the key to processing and analyzing large data streams and identifying what valuable insights there are. In the customer service industry, machine learning can help agents with predictive analytics to identify common questions and answers. This technology may even catch what the agent may have missed when communicating.
6. Natural language processing: many customer service teams use natural language processing in their client or voice programs. By transcribing phone, email, chat, and SMS interactions and then analyzing the data to identify specific trends and topics, the agent responds to client needs more quickly.
7. IVR automation: while interactive voice response (IVR) systems have been automating simple routing and transactions for decades, new conversational IVR systems use AI to complete tasks. Everything from verifying users with voice biometrics to telling the IVR system directly what needs to happen using natural language processing makes the customer experience easy.

How we interact with clients today differs significantly from what we did many years ago. Processes are much faster, easier, and more efficient. With multiple use cases of AI in customer service and more, customer service teams need to think more critically, solve higher-level problems, and use every tool available to create an unforgettable customer experience.

Main challenges of AI in customer service

While AI continues to develop and evolve in its capabilities, specific key issues confuse the user instead of helping to use AI in customer service that has yet to be resolved. Let’s talk about the three main disadvantages of AI:

• Lack of emotion and empathy: there is no human thinking in AI, and as a result, it appears as an insensitive system with no emotion or empathy, which are the driving forces behind customer service.
• Inability to localize a conversation: if you want AI to serve clients in a foreign language, it’s not as easy as translating text. In addition to changing the script, the website must be culturally compatible with the target audience.
• Significant implementation costs: the cost of creating a chatbot depends on its functionality and the requirements of your business.

Technologies are developing every day, and the risks are becoming less significant. You can always switch to another solution if you feel a particular tool is not worth it.

Even when communicating with human representatives, AI can improve the customer experience by automatically extracting information and suggesting solutions so that the agent can provide answers to the client much faster. By automating routine tasks, AI allows customer service agents to spend more time on the most challenging problems that human agents can only solve instead of repeating the same answers to the same basic questions that a chatbot can answer for an agent.