How AI Benefits Customer Service

How AI Benefits Customer Service and How it is Used in Contact Centers

Whether you like it or not, Artificial Intelligence has already deeply penetrated and transformed many aspects of business operations – customer service is no exception. As more AI customer service technologies are stepping into the spotlight, AI-driven chatbots are no longer the only tools customer service teams can leverage to optimize service operations.

With customer expectations rising faster than innovations are adopted, it’s about time to embrace AI and unlock new perspectives to improve the experience for both your support reps and your customers. So how can AI help customer service? In this blog, we’re about to explore in-depth how AI can be used in customer service and support to set the stage for improved support efficiency and better CX.

Top 8 Benefits of Using AI in Customer Service

  1. An ability to provide customer support 24/7/365
  2. Fewer requests that require human assistance
  3. Reduced handle times and increased FCR rates
  4. Improved customer service experience
  5. Higher efficiency of support agents
  6. Reduced agent workload and burnout
  7. More actionable insights into customer interactions
  8. Reduced customer support costs

Using contact center solutions with AI capabilities truly brings a wealth of benefits to the table when it comes to handling customer service interactions. From faster response times and enhanced experiences to reduced burden on your agents and improved cost-efficiency – let’s get straight to the point and outline these benefits one by one.

1. An ability to provide customer support 24/7/365

By using AI-powered self-service tools like AI chatbots, virtual agents, and voice bots, businesses can expand their customer service and support capabilities beyond their standard business hours while consumers get the privilege of being able to get customer support round-the-clock, whenever they need it.

Not only are these channels super convenient for consumers by being immediately available 24/7. But it also means that your business can better live up to customer expectations since self-service support and AI chatbots, in particular, are becoming increasingly preferred by consumers. In fact, Gartner predicts that by 2027, chatbots will become the primary customer service channel for nearly a quarter of organizations.

2. Fewer requests that require human assistance

As technology evolves, AI chatbots are becoming more intelligent by getting the ability to mimic human behaviors and enable natural, human-like conversations. And though chatbots might not yet be able to resolve complex support requests, failing in cases where human judgment and empathy are critical, they are an excellent way for consumers to get answers to simple queries. For businesses, that means fewer repetitive customer queries and customer support requests that require human-assisted support.

3. Reduced handle times and increased FCR rates

Numerous studies have proved that consumers want their requests answered and resolved quickly and, most importantly, during a single interaction so they don’t have to reach out to customer support again and again regarding the same issue. In fact, Salesforce found that 83% of consumers expect to solve complex issues by speaking to one person, yet only 13% say it takes little effort to get their issues resolved. With intelligent AI routing that ensures customers are connected to the most relevant reps and AI agent assist tools, you can improve your First Call Resolution (FCR) rates, Average Handle Time (AHA), and Customer Satisfaction Scores (CSAT).

4. Improved customer service experience

A happy customer interacting with an AI interface, symbolizing improved customer service experiences.

When AI is integrated into your customer service process, it ultimately helps improve customer service and enhance the customer experience – and consumers have actually become more responsive to AI solutions, too. According to a Salesforce study, 69% of consumers say they are open to the use of AI to improve their experiences. AI agent assist and sentiment analysis are great examples of customer service AI solutions that can help support reps deliver a more efficient and more personalized service experience to customers.

5. Higher efficiency of support agents

Accenture predicted nearly a decade ago that the impact of AI technologies on business is expected to boost labor productivity by up to 40%. How does AI improve the productivity of customer support agents? By simply reducing the amount of manual tasks like routing and categorizing customer requests, cutting down on the number of requests that require human support, or helping agents respond faster with AI-generated suggestions, AI customer service solutions can make support reps much more efficient and productive, enabling them to focus on more complex, higher-value tasks.

6. Reduced agent workload and burnout

Every customer service professional knows that burnout is a very real issue in the contact center industry. A study by Toister Performance Solutions revealed that 59% of contact center reps are at risk of burnout, with 28% facing a severe burnout risk. Lots of repetitive tasks, having to deal with frustrated customers, and a lack of adequate support from management are just a few reasons leading to increased burnout. While managing employee burnout requires a holistic approach, implementing AI solutions into your customer service operations can help you reduce the workload on your support reps, contributing to reduced burnout.

7. More actionable insights into customer interactions

When you incorporate AI sentiment analysis into your call center quality assurance process, you can gain deeper insights into every interaction by tracking customer sentiment scores. That can help you better gauge customer satisfaction levels in addition to measuring CSAT (Customer Satisfaction Scores, CES (Customer Effort Scores), and NPS (Net Promoter Scores). Besides that, tracking customer sentiment scores helps managers better assess the performance of individual reps and see where they might need additional training and coaching. What’s more, beyond understanding present customer sentiments, predictive analytics tools can analyze historical sentiment data and help you predict future trends.

8. Reduced customer support costs

Cost savings in customer support due to AI.

Using self-service AI chatbots and voice bots to help customers find information and resolve issues on their own provides many cost-saving opportunities for contact centers. Firstly, that can naturally reduce the inbound call volume and thus lower your customer support costs. Secondly, chatbots and voice bots are automated solutions that can work 24/7/365, unlike human agents, and can handle support tasks normally done by several agents. It means you can save on labor costs – and that can be significant if you consider the cost of hiring, training, and retaining customer service reps.

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Examples of Using AI Solutions in Customer Service and Support

Let’s now go through the examples of using AI solutions in customer service and explore how they can help you automate processes, streamline your service operations, improve your customer service quality, enhance CX, and increase the overall efficiency of your support reps. Here we go:

AI routing and IVR (Interactive Voice Response) 

Call routing and Interactive Voice Response (IVR) systems are at the core of efficient inbound call management. When AI came into the mix, these systems became much more intelligent and effective. AI-driven call routing (which is also known as predictive behavioral routing) and AI-enabled IVR software systems can analyze customer data like customer history, past behaviors, preferences, and other historical and real-time data to better understand customer intent and route the caller to the best-suited customer service representative. With AI routing and speech-enabled IVRs, you can deliver a more tailored customer experience and achieve higher CSAT scores.

AI predictive dialing

Though AI predictive dialing software systems are mostly used by sales teams for outbound lead generation and outbound sales, these tools can also be helpful for customer service teams. AI predictive dialers employ NLP (Natural Language Processing) and ML (Machine Learning) algorithms to ‘predict’ agent availability and initiate multiple simultaneous outbound calls per agent. Once the agent completes their current interaction, they are instantly connected to the next call. That means minimized idle time between calls and increased agent productivity.

VoiceSpin’s AI Dialer goes even further than that. It scores and prioritizes leads and matches them with the best-suited agents who are most likely to close a successful sale. Customer service teams can leverage the tool to proactively reach out to customers for various purposes (follow-ups, customer surveys, service renewal reminders, critical notifications, etc.). With the AI predictive dialer, your service reps can connect with more customers in less time, increasing the efficiency of their outbound calling efforts.

Generative AI

Generative AI is already transforming the customer service industry, enhancing the efficiency and productivity of customer support reps with AI-powered assistance. By using Natural Language Processing and Machine Learning to analyze conversations between agents and customers, Generative AI retrieves relevant data from your knowledge base and CRM and generates ready-to-send responses that your reps can then evaluate, edit, and use without having to waste precious time searching for the necessary information manually or even type anything before hitting ‘send’. That truly saves a bunch of time and effort for your support team. 

AI chatbots and AI voice bots

When talking about using AI in customer service, chatbots are what usually comes to mind first. And no wonder because chatbots are one of the first AI solutions implemented to enhance customer service automation. We’ve already mentioned earlier in the article how AI chatbots can improve your customer service accessibility and streamline your customer support operations. AI chatbots and voice bots handle customer inquiries and generate human-like responses through what is known as Conversational AI. Many organizations are already actively using AI chatbots and voice bots and seeing impressive results.

AI Speech analytics

AI speech analytics tools are gradually becoming a must-have in contact centers and call centers. Speech analytics solutions use AI, NLP, and speech recognition technologies to analyze and extract valuable information from spoken conversations, helping managers get deeper insight into customer interactions. It helps them better understand customer behavior, trends, and customer pain points and assess agent performance and overall efficiency of their customer service operations.

E.g., with VoiceSpin’s AI Speech Analyzer, you can monitor 100% of your calls to ensure a continuous QA process. Among other capabilities, the tool can help you prevent non-compliance issues (which may result in hefty fines) through keyword spotting, real-time alerts, and call whispering features.

Sentiment Analysis 

As part of speech and voice analytics, sentiment analysis solutions use AI and NLP, ML, and computational linguistics to capture customers’ emotions and attitudes by analyzing vocal characteristics of the spoken language, such as pitch, tone, volume, level of stress, and other variables. Based on that, sentiment analysis tools assign a sentiment score to each conversation by labeling it as positive, neutral, or negative. How does it help in customer service improvement? By gauging sentiment in customer-agent interactions, you can better understand customers’ perceptions of your products or services. In addition, you can identify agent training gaps and opportunities for improving your processes.

The Future of AI in Customer Service. Will AI Replace Customer Service Agents?

AI and human agents working side by side.

What does the future hold for Artificial Intelligence in the customer service industry? Obviously, AI is here to stay, and we should definitely embrace its potential to transform and improve the way we deliver customer service. AI-driven customer service solutions are already being widely adopted by forward-thinking businesses and organizations across many industries, and this adoption will only grow exponentially in the coming years.

When talking about the future of AI in customer service, the next essential question that follows is whether AI is going to eventually replace human expertise in customer service. Luckily, it seems that most customer service professionals see AI as a positive influence on their work rather than a threat to their jobs. According to a HubSpot study, despite the fact that 39% of customer service professionals are concerned about AI replacing their job in the next couple of years, 78% of CS experts say AI/ automation helps them spend more time on the most important parts of their role and makes them more efficient, while 62% agree that these tools help them understand their customers better.

That being said, though AI tools play a significant role in automating and streamlining customer service operations (while also being great time-savers and efficiency boosters for customer service reps), they aren’t likely to entirely replace human agents any time soon due to the limitations and challenges involved in using them. Even advanced customer service AI solutions are still far from delivering the level of personalization a human agent would – and 45% of CS professionals believe that maintaining a personalized experience while using AI remains the biggest challenge.

On top of that, AI tools cannot replace human empathy and aren’t able to resolve complex issues, such as those that involve complaint resolution or escalation management. A SurveyMonkey report also revealed that around 90% of people still prefer to get customer service from a human agent rather than a chatbot, and 61% of the surveyed consumers believe humans understand their needs better than AI.

Potential Challenges and Limitations of Using AI in Customer Service

Let’s take a closer look at some of the biggest challenges and limitations of using AI-powered chatbots in customer service:

Inability to resolve complex issues

Based on the stats published by HubSpot, 40% of consumers don’t care if they talk to an AI chatbot or a real customer support rep as long as their questions are answered quickly. However, not all customer service requests require a simple and straightforward answer that a chatbot can easily provide by simply pulling the right information from your internal knowledge base and CRM. In many cases, customer service requests are much more complicated – and that’s where AI chatbots may fail. A quick example is when a customer encounters a rare tech issue that is not documented in your knowledge base.

Lack of a personal touch

Will AI replace customer service where a personal human touch is needed? Absolutely not. When a customer requests to escalate their issue to the manager, when a customer wants you to violate the company’s policy, or when a customer asks for a significant discount because they’ve been loyal to your brand for years are just a few examples of customer service scenarios that require a human touch AI bots can’t offer.

Customer preference for human interaction

Even though most of today’s tech-savvy consumers generally view AI-powered customer service interactions positively, many still prefer to talk to a human agent, even when they have to wait for it. Callvu’s AI in Customer Service report revealed that 81% of consumers would wait to speak with a live agent for at least a few minutes versus engaging with an AI assistant immediately. Additionally, based on HubSpot’s stats, 62% of consumers prefer speaking with a human agent over a bot when they have difficult problems or complex questions.

Lack of emotional intelligence

Despite its advanced AI capabilities and machine learning algorithms, AI bots fall short when it comes to being empathetic because they still lack emotional intelligence. That means they cannot fully comprehend emotions and respond to emotional cues in the way that human agents can. For example, if a customer is frustrated or upset, an agent can easily pick up on these cues and adjust their language and tone accordingly because humans possess a natural ability to be empathetic. And this is often the key to delivering quality service and building loyalty.

Leverage VoiceSpin’s AI Contact Center Solutions to Ramp up Your Customer Service

Implementing AI solutions and incorporating them into your customer support process doesn’t have to be overwhelming and complicated. The first step is learning more about how AI tools can actually improve your customer service operations, optimize issue resolution, and give a boost to your support team’s efficiency. Now that you’ve learned a little more about that from what we’ve outlined above, the next logical step would be to explore the variety of providers offering customer service AI solutions. And VoiceSpin does have something to offer:

  • An AI predictive dialer that connects leads and customers to the best-suited agents, ensuring more positive outcomes from your outreach efforts;
  • An AI Speech Analyzer that provides deeper insights into your customer-agent interactions and helps prevent non-compliance issues;
  • AI-powered chatbots and voice bots that can handle your support request 24/7, extending your customer service availability and readiness.

Book a demo call now and learn more about how you can improve your customer service and customer experience while also making life easier for your customer support team with VoiceSpin’s AI contact center software solutions.

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Share this article:

  • How AI Benefits Customer Service and How it is Used in Contact Centers
    1. Top 8 Benefits of Using AI in Customer Service
    2. 1. An ability to provide customer support 24/7/365
    3. 2. Fewer requests that require human assistance
    4. 3. Reduced handle times and increased FCR rates
    5. 4. Improved customer service experience
    6. 5. Higher efficiency of support agents
    7. 6. Reduced agent workload and burnout
    8. 7. More actionable insights into customer interactions
    9. 8. Reduced customer support costs
    10. Examples of Using AI Solutions in Customer Service and Support
    11. AI routing and IVR (Interactive Voice Response) 
    12. AI predictive dialing
    13. Generative AI
    14. AI chatbots and AI voice bots
    15. AI Speech analytics
    16. Sentiment Analysis 
    17. The Future of AI in Customer Service. Will AI Replace Customer Service Agents?
    18. Potential Challenges and Limitations of Using AI in Customer Service
    19. Inability to resolve complex issues
    20. Lack of a personal touch
    21. Customer preference for human interaction
    22. Lack of emotional intelligence
    23. Leverage VoiceSpin's AI Contact Center Solutions to Ramp up Your Customer Service
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