Customer Service AI: How It Works & Why You Need It

As the demand for improved and personalized customer service grows, organizations are adopting AI to help bridge the gap.

Advancements in artificial intelligence continue to pave the way for increased efficiency across the organization, especially in customer relations. Chatbots continue to be at the forefront of this change, but other technologies such as machine learning and interactive voice response systems create a new paradigm for what customers — and customer service agents — can expect.

And while not every piece of technology is right for every organization, AI will continue to be central to the future of customer service.

Understanding customer service AI

There are many different ways you can use AI in customer service. For example, you can embed AI-powered chatbots across channels to instantly streamline the customer service experience. Beyond answering common questions, these chatbots can greet your customers, serve up knowledge base articles, and guide them through common business processes.

They can also send out a field technician for field requests and route more complex questions to the right person.

AI as a service has already become an integral part of customer care operations. The importance of artificial intelligence customer service is driven by flagship technologies such as natural language processing (NLP), speech recognition, machine learning (ML), etc. AI-based customer support is taking the stress off the agents by enabling seamless customer experiences.

In the coming years, AI will be more acknowledged and appreciated in the context of digital customer experience. The output of artificial intelligence is becoming universal, irrespective of business aspects, that rely on the latest technologies, and here, customer support is no exception. These kinds of resources are becoming universal in any aspect of business that relies on modern technology.

Examples of AI in customer service

Here are 10 examples of the future of AI in customer service.

Chatbots

One of the most common uses of AI in customer service is chatbots. Businesses already use chatbots of varying complexity to handle routine questions such as delivery dates, balance owed, order status or anything else derived from internal systems. By transitioning these frequently asked questions to a chatbot, the customer service team can help more people and create a better experience overall.

All of these while cutting operational costs for the company.

Machine learning

At its core, machine learning is key to processing and analyzing large data streams and determining what actionable insights there are. In customer service, machine learning can support agents with predictive analytics to identify common questions and responses. The technology can even catch things an agent may have missed in the communication.

Additionally, machine learning can be used to help chatbots and other AI tools adapt to a given situation based on prior results. It can ultimately help customers solve problems through self-service.

Agent assist

In many modern omnichannel contact centers, agent assist technology uses AI to automatically interpret what the customer is asking, search knowledge articles and display them on the customer service agent’s screen while they’re on the call. The process can save time for the agent and the customer, and it can decrease average handle time, which also reduces cost.

Robotic process automation

Robotic process automation (RPA) can automate many simple tasks that an agent used to perform. Automating bots to focus on updating records, managing incidents or providing proactive outreach to customers, for example, can drastically reduce costs and improve efficiency and processing time.

One of the best ways to determine where RPA can assist in customer service is by asking the customer service agents. They can likely identify the processes that take the longest or have the most clicks between systems. Or they may suggest simple, repetitive transactions that don’t require a human.

When prioritized and deployed correctly, this type of business process improvement can save customer service companies millions of dollars each year.

Self-service

Customer self-service refers to customers being able to identify and find the support they need without relying on a customer service agent. Most customers, when given the option, would prefer to solve issues on their own if given the proper tools and information.

As AI becomes more advanced, self-service functions will become increasingly pervasive and allow customers the opportunity to solve concerns on their schedules.

Natural language processing

Many customer service teams use natural language processing today in their customer experience or voice of the customer programs. By having the system transcribe interactions across phone, email, chat and SMS channels and then analyze the data for certain trends and themes, an agent can meet the customer’s needs more quickly.

Previously, analyzing customer interactions was a lengthy process that often involved multiple teams and resources. Now, natural language processing eliminates these redundancies to create deeper and more efficient customer satisfaction.

AI training

As the COVID-19 pandemic forced employees into remote positions, many training teams began using AI to construct simulations to test employee aptitude for handling various situations. Previously, the training involved a blend of classroom training, self-paced learning and a final assessment — a routine that’s much harder to implement in remote or hybrid offices.

With AI taking the role of the customer, new agents can test out dozens of possible scenarios and practice their responses with natural counterparts to ensure that they’re ready to support any issue a user or customer may have.

Smart speakers

The practical applications for organizations and customer service teams are still a work in progress, but smart assistants such as Alexa, Google Assistant and Siri are an exciting avenue for personalized service. Customers appreciate and prefer when an organization communicates via their preferred platform, and for some people, that may be via their smart home device.

Imagine a future where a user can bypass a phone call or email and troubleshoot any product or service concern via a simple question to their smart speaker. Simplified communications like this could be the difference between a satisfied or frustrated customer.

IVR automation

While Interactive Voice Response (IVR) systems have been automating simple routing and transactions for decades, new, conversational IVR systems use AI to handle tasks. Everything from verifying users with voice biometrics to directly telling the IVR system what needs to happen with the help of natural language processing is simplifying the customer experience.

Some companies turn to visual IVR systems via mobile applications to streamline organized menus and routine transactions. Blending many of these AI types together creates a harmony of intelligent automation.

Sentiment and advanced analytics

Using sentiment analysis to analyze and identify how a customer feels is becoming commonplace in today’s customer service teams. Some tools can even recognize when a customer is upset and notify a team leader or representative to interject and de-escalate the situation. In conjunction with a voice of the customer tool, sentiment analysis can create a more honest and full picture of customer satisfaction.

Vendors such as Brandwatch, Hootsuite, Lexalytics, NetBase, Sprout Social, Sysomos and Zoho offer sentiment analysis platforms that proactively review customer feedback.

Benefits of AI in customer service

There are several benefits that AI-based customer service offers to businesses. Here are some of the most popular ones below:

24×7 customer service

Offering around-the-clock customer support is imperative particularly for global brands as they have customers from different continents and time zones. Besides, modern-day customers do not want to wait. If they feel something is wrong with the product/service at midnight, they would like to reach the brands and raise the concern then and there. As well as they prefer different channels to interact and engage with customer support.

AI is making this possible for businesses by allowing them to answer through self-directed knowledgebase – FAQs or chatbots. Businesses can stay online 24×7 and provide support to the customers.

Businesses are adopting AI tools in their customer service operations to polish their interaction. This means that the synergistic approach throughout touchpoints leveraging AI makes the entire process seamless.

Reduce AHT (Average Handling Time)

Reducing average handling time is one of the most extraordinary benefits of AI-powered customer support. With traditional customer service, the customers used to complain about the wait times, to, obtain support. But today, AI-chat bots are interacting with customers and resolving their basic concerns and queries to a great extent in real time.

Therefore, customers do not have to wait for long in the queue to engage with customer service agents.

Also, customers are getting notifications and reminders about products, offers, and deliveries proactively. AI-powered customer service keeps the customers on priority.

Managing huge amounts of data

As customer interaction grows with businesses, it produces the generation of data in large volumes. The limitations of humans prevent endless processing of data systematically. That is where artificial intelligence tools come into play. Accumulating such large volumes of data would be unusable without AI.

By processing this huge quantity of data with AI, businesses can gain powerful predictions and insights into customer behavior. This enables businesses to resolve the most complex customer concerns, inquiries, and complaints. It also helps in formulating targeted marketing campaigns to boost sales.

It is essential to have a robust CRM tool (Customer Relationship Management) in place for the obtained huge customer data as Excel sheets will make you suffer in real-time customer service operation.

Omnichannel support

Multichannel customer support allows customers to interact with brands at their preferred touchpoints. This has brought a positive outlook toward brands. Customers can always reach a brand in one way or another. But again, multichannel support comes with the challenge of processing a large volume of data and different channels to cover.

AI can quickly accumulate and prepare data from various touchpoints and centralize all the information about each customer or client and their interactions through multiple channels. With this omnichannel approach, businesses can provide superb customer experiences. A powerful CRM at the backend of any business can save all the customer data as a single source, from where agents can access it and make work quite efficient.

Artificial Intelligence empowers businesses to manage customers better and their expectations irrespective of the touchpoint.

How to use generative AI to improve customer service

Here are a few ways that AI can help organizations provide even better service to their customers:

Search for answers. As your agents or customers are looking for answers to a question, AI in customer service can surface a generated answer from your knowledge base, directly into the search page — saving everyone time.

Create work summaries and mobile work briefings. Customer service AI can drive agent productivity by automating the time-consuming but crucial task of writing wrap-up summaries based on case data and history. This is especially helpful in the field. You can summarize the most relevant data to start the job — saving your frontline workers time.

Preserve and share knowledge across your business. You can connect a generative AI tool to your service console and have it create the first draft of your knowledge base article based on conversation details and CRM data for your experienced agents to review. This will save you time and help you get your articles out faster. An extra bonus: you can also use these knowledge base articles to help customers find their own answers to questions in a self-service portal.

Quickly generate personalized replies to service inquiries. This technology can help agents respond to service questions with personalized prompts. AI can generate these responses based on relevant customer data, knowledge articles, or trusted third-party data sources on any channel.

Customer Service AI: How It Works & Why You Need It

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Understanding customer service AI