AI in Customer Support: Key Trends, Use Cases and Benefits

There was a time when meeting customers’ expectations used to be a cakewalk by delivering just high-quality products and services that used to result in a win-win situation for both sellers and customers. However, with the rise of digital technologies and industries becoming more competitive, there is cut-throat competition to deliver the best customer experience. Utilizing AI in customer support systems is one of the best ways to meet customer needs and optimize processes.

With the advent of GenAI, conversational AI has taken a new shape, and it can easily answer customer inquiries. Using AI in sales and customer support will also free up your support agents to work on more complex and productive tasks. Customer service professionals have always been found struggling with a limited budget to deliver high customer value. But now, with the increasing role of AI in customer support, things have become easier and simpler.

In this article, we will go through all the major aspects of AI in customer support, including key trends, use cases, benefits, and more.

Do you know 72% of customers say that they will remain loyal to companies that provide faster service?

On the other side, 69% of the service agents say it is difficult to manage equilibrium between speed and equality.

What is AI in Customer Service?

The role of AI customer support encompasses many different scenarios. For instance, you can leverage AI-powered chatbots in your applications to deliver fast and smooth customer support service. These AI-powered chatbots will not be just limited to greeting your customers and resolving only generic inquiries but also building up a knowledge base using machine learning technology. The knowledge base will empower the chatbots to resolve even highly anomalous or out-of-the-blue queries of the customers.

A decade ago, when a customer wanted to return a pair of shoes and require some help from the online store, it would always take at least half an hour to get proper guidance.

But now, you can hire an AI development company that will build AI-based customer support systems that can deliver personalized responses in seconds. AI in customer support gives you a virtual buddy who is not only knowledgeable but also understands your exact needs and preferences.

Market Statistics of AI in Customer Support Systems

You would be surprised to know that by 2025, it is projected that the chatbot market will grow significantly higher to a valuation of approximately 1.25 billion USD. This is a huge increase, considering that the market value in 2016 was just 190.8 million USD.

AI is required in customer support, mostly in retail industries. As per the Precedence Research report, 21.50% of apps are segmented into customer relationship management (CRM). Furthermore, the use of chatbots in the hospitality sector was expected to increase by 53% during the course of 2022, according to a January 2022 global poll of hotel professionals by Statista.

As per the study of Tidio, nearly 62% of the customers would prefer to choose an AI-based chatbot for customer service instead of prolonged waiting for humans to respond to their queries.

Top AI Use Cases in Customer Support

The use of AI in customer support involves many different purposes or domains of business. Let’s understand each in a bit of detail:

1. Customer Inquiries and Support:

The Gen-AI-based conversational AI solutions are built to manage highly complex customer queries and leverage natural language processing technology (a subset of AI) to provide customer support. It also utilizes interactive decision trees and access to relevant data sources. That’s how an AI-based customer support system provides accurate responses and guides customers through issue resolution steps, resulting in effective and efficient support for complex customer queries.

2. Marketing and Sales:

There is a major role of AI in customer support by acting as an agent for product recommendations, cross-selling, and upselling. It can utilize customer data, preferences, browsing history, and other data points to offer personalized recommendations. The AI-based customer support will suggest highly related products during the customer journey. It increases the ticket size, resulting in higher order value and sales.

3. Booking and Reservations:

The hospitality industry is leveraging AI to build customer chatbots for booking and reservation processes. With AI, customers can seamlessly and conveniently make reservations. They can also check availability and receive booking confirmations. Here are the three major examples of how AI-based customer systems can assist in the booking and reservation process:

Reservation Inquiries:

You can hire AI development company that provides SaaS development services to build AI solutions offering high interactions. With this, the customers inquire about hotel room availability, rates, amenities, and much more. It will provide real-time responses based on the hotel’s booking system and help customers find their best preferences.

Assistance in Booking:

Once the customer decides to make a reservation, the AI chatbot can guide them through the booking process by collecting necessary details like check-in and check-out dates, as well as payment details.

Confirmation and Reminders:

The use case doesn’t end at booking, but AI can also be used to generate a confirmation receipt and send it to the customer through email or message. The AI-based chatbot will also send reminders to the customer closer to the check-in date.

4. Order Tracking and Delivery Updates:

You can use an AI bot to deliver real-time updates of shipment, delivery, and other stages to customers. After a consumer places an order, the chatbot can automatically send a confirmation message with order details such as the order number, items requested, and expected delivery time.

The AI tool will also provide a comprehensive summary of an order and request confirmation from the customer. The real-time updates will also be in sync so that customers can check the status of the order at any time.

5. Onboarding and Training:

The AI-based customer support systems can also be used for smooth onboarding and provide training on certain specialized products. The chatbots can be used to create interactive tutorials for new customers to help them learn how to use the product or service.

Also Read: AI in Telecommunications: Key Trends and Benefits

Benefits of Using AI in Customer Support:

1. Speed and Efficiency:

AI in customer support can be used to give quick attention to customer queries, providing immediate responses without requiring human intervention. Their automated and efficient nature allows them to swiftly resolve general queries, leading to quick resolution and improved customer satisfaction.

2. 24 x 7 Availability:

Human-based support is limited to a particular period of time; thus, either required to hire extra people to work different shifts or stop support. However, with AI-based customer support, you can deliver exceptional customer service 24 x 7 without any breaks. The AI-based chatbots are always there to answer user queries, regardless of the time and day or day of the week. Thus, customers don’t need to wait for working hours only to access support.

3. Personalization:

To offer personalization, AI leverages customers’ data from various sources, including browsing, searching for products, and other data points. It can do customer profiling to collect and analyze customer data and create customer profiles.

The NLP-based chatbots can understand human language, including sentiment, intent, and tone; this allows them to deliver personalized responses. Also, NLP helps to maintain context within a conversation, allowing them to remember and reference previous interactions.

Conversational AI solutions can be developed with interactive decision trees that lead clients down a tailored route of questions to better understand their needs and give relevant solutions.

4. Cost-Effectiveness:

There will be much less operational cost in delivering better customer service by using conversational AI. It can increase profitability by automating repetitive tasks, providing 24/7 support, and handling a large volume of inquiries.

5. Scalability:

AI-based solutions are capable of handling multiple queries at once, so no customer has to wait in a queue for a turn to get his/her queries resolved. Also, you don’t need to increase or decrease the size of your customer support team frequently.

6. Improved Data Collection:

For a better customer experience, AI-based chatbots will collect data about customers, such as inquiries, preferences, and behavior. These insights would be helpful for businesses to identify unique trends, patterns, and customer preferences. This will help further improve business operations, product development, and marketing strategies for better decision-making and better customer engagement.

7. Improved Brand Image:

The D2C brands can greatly benefit from AI-based customer service as it will improve the brand image by providing modern and innovative customer-based solutions through cutting-edge technology.

Examples of AI in Customer Service

Regardless of your industry, AI and machine learning solutions will transform your customer service. Here are the major examples:

1. Content Generation:

Generative AI can be used to analyze customer conversations, extract relevant details, and generate human-like replies to customers. It results in a better experience, less time, and highly relevant answers.

2. Chatbots:

AI-powered chatbots are on the rise in various industries, particularly in the D2C segment. These chatbots can provide instant responses and assist with tasks like order tracking, product recommendations, and troubleshooting. The AI-powered chatbots are available 24/7 so customers can get their queries resolved at any instance of time.

3. Sentiment Analysis:

In order to determine customer sentiment, AI-powered sentiment analysis systems track and examine reviews, social media interactions, and customer comments. This enables businesses to respond to consumer issues, pinpoint areas for development, and offer individualized experiences according to client preferences.

4. Recommendation Systems:

AI-based recommendation systems leverage various forms of customer data to provide personalized product or content recommendations. It improves companies’ upsell and cross-selling opportunities.

5. Self-Service Solutions:

AI-powered self-service systems, such as knowledge bases or FAQs, use natural language processing to interpret user inquiries and give relevant information or troubleshooting procedures. Customers and representatives can get answers quickly without requiring human intervention.

Learn More: AI in Banking: Effective Use Cases that Drive Results

Challenges and Considerations in AI Implementation

Though there are a myriad of advantages to implementing AI in customer service, there are certain challenges that we can’t ignore. These hurdles must be overcome in order to realize the full potential of AI.

1. Technological Hurdles:

The foremost challenge in implementing AI in customer service is to make it fit into the existing infrastructure. There are a lot of companies that are still using highly outdated systems that are not designed for the amalgamation of AI. Implementation often requires significant investments in new technologies along with adjustments to existing systems. It is both time-consuming and expensive.

However, a proficient AI development company like ours can bring workflow automation services to ensure the systems work correctly and optimally.

2. Data Privacy and Security:

As we have mentioned several times, AI-based customer service will leverage customer data for personalization, and this raises the question of data privacy and security. All companies must adhere to all data privacy and security regulations, such as GDPR.

In addition to the potential for legal repercussions, breaking these rules can erode consumer confidence over time. As a result, businesses need to put strong security measures in place and be open about how they handle and safeguard consumer data.

3. Acceptance:

After the implementation, the challenges are still there. There are also human factors to consider while implementing AI. Employees and customers may have doubts about the new technology. Employees may be concerned that AI will harm their careers or change their tasks. Customers, on the other hand, may be skeptical about engaging with a machine rather than a person.

4. Lack of human touch:

AI-based support lacks empathy, which a customer prefers in many cases. For common queries, these AI-based tools are highly efficient, but for certain queries that require emotional intelligence and real conversational abilities that human agents can offer in certain situations, AI still can’t replace humans.

Wrapping Up

In this article, we have gone through all the major use cases, benefits, and challenges of implementing AI in customer support. AI-based customer support is transforming customer service by providing quick and smart assistance to customers, improving customer satisfaction, and reducing operational costs.

At Octal IT Solution, we have tremendous experience in building AI-based customer support solutions from scratch. Our AI developers have vast experience in developing SaaS products, tools, and other products based on NLP, ML, and other subsets of AI. Let us know your requirements.

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