If you’re in business, you probably know that the quality of customer support is directly tied to customer satisfaction and loyalty. And for any business, keeping the wheels of exceptional customer service rolling is vital. But, it can be overwhelming.
There’re so many customer care touch points to cater to — and at a high level — which means expensive tools and piling more costs in labor or even staff training.
Customer service AI is a way to keep these concerns at bay while significantly improving your customer experience. From a strictly value-based perspective, this makes AI the most affordable and hardworking employee your company can hire.
So, AI in customer service? Defo a no-brainer. But let’s distil the “whys” and “hows” a bit more precisely.
Artificial Intelligence in Customer Support you say?
Ever since AI marked its debut in customer service with ELIZA — a chatbot created in the mid-1960s to help doctors diagnose patients and recommend solutions —, contact centers have jumped on this revolutionary technology to transform their processes.
Today, Artificial Intelligence in support environments comes in varying forms and sizes depending on the task and it has become a way to upscale performance while cutting back on operational costs. From chatbots to interactive voice response systems and self-service, businesses can now interact more efficiently with customers across different channels, with a 24/7 availability, global reach, and in different languages.
Whether working alongside human support agents, catering to mundane issues, or crunching the numbers to deliver support insights, AI can take your customer care to the next level and impact your bottom line.
Examples of AI in customer service
Given the widespread use of AI in customer service, you’ve probably encountered one or more of these use cases:
Chatbots are gaining wide adoption in customer service delivery. They’re a computer software that provides automated responses to customers’ routine questions via chat.
With chatbots, businesses can optimize the customer experience by preempting customers’ queries, providing quick solutions, and referring them to human support agents if necessary.
Many customers today prefer to jump on the option of resolving their complaints themselves rather than rely on a service agent. in that regard, self-service is another familiar depiction of AI in support environments. Here, the company initiates software that allows the customer to identify issues and find help without the assistance of a company representative.
With agent-assist, AI technology provides your team members with valuable information about the customer’s complaint. It automatically processes the query by researching it and playing the right solutions on the agent’s screen.
Agent-assist empowers support agents with automated assistance, recommendations, and next-best actions, whether during digital chat interactions or live calls.
Machine learning is a crucial mechanism for analyzing large data flows and pinpointing what valuable insights can be gleaned from it.
This AI application can, for example, enable predictive analytics, identify FAQs (Frequently asked questions) and provide adequate responses about current issues based on prior issue history.
Natural language processing
Natural language processing allows companies to examine the speech interactions of their customers. Here’s how it works: the system transcribes communications across different platforms and analyses the data to discover the trends or themes a customer often interacts with.
Ultimately, the results of such analysis point service agents toward the best ways to enhance the customer’s experience.
Naturally, businesses are concerned about meeting and even exceeding customer expectations. Many companies, for example, use AI software to gather and analyse customer feedback and transport the data to a customer care agent, who is in the best position to provide a suitable response swiftly.
This could also come in the form of speech analysis, where communications (between support agents and customers) are transcribed and analysed to dig out useful insights.
Emotional Intelligence AI
This is another type of AI technology most commonly seen in call centers. The best way to understand emotional intelligence AI is with an example.
A conversation between a support agent and a customer may have long pauses or cues of customer frustration which the agent may miss during the call. This AI is usually trained to recognise pitch changes, tones, and linguistic nuances across cultural contexts. As such, it can be a very reliable indicator of customer satisfaction levels.
The benefits of customer service AI
By implementing AI solutions in your contact center you can
Improve your First Response Time (FRT)
First Response Time is a customer service KPI that tracks how much time has passed from the moment a customer first submits their case and one of your agents responds to it. Your goal should be to keep your FRT as low as possible. To achieve that you have to increase agent focus and free up agent time. AI applications are great tools to help with this task. A chatbot, for example, can provide answers to basic customer inquiries fast and effortlessly. As a result, you will increase your agents’ capacity to respond faster to more complex and challenging issues that require human-to-human communication.
Relieve contact volumes
According to research data, a staggering 74% of customer service leaders globally have seen an increase in support volumes across digital channels. So, what do you do when your inbound customer requests spike but at the same time you are pressured to keep costs at bay? You deploy a chat bot. Or, you build a knowledge base. Or, both.
The point is, AI-powered solutions can help you deal with high contact volumes more effectively by offering self-service options that free-up agent time.
Enable skill-based routing
What if you could crunch down the data and match customer service requests with agents whose skill-set revolves around the specific subject matter of each request? AI can map out agent skills based e.g. on sentiment analysis. You can use this information to assign incoming tickets to specific agents using a variety of methods such as decision trees, text analysis, or keywords.
If you’re looking for a recipe for successful customer service, well, look no further. This approach can increase both customer satisfaction and your First Contact Resolution rates. Why? Because you redirected the customer request to the team member who is the most equipped to handle it effectively.
Boost agent productivity
A truly high-performing customer service organization is fuelled by agent productivity. Here’s how AI can enhance your team’s performance:
1. Streamlining workflows
AI augments the efforts of your team, thus improving productivity. Allow your AI chatbot to handle general inquiries and empower your agents to operate in a streamlined workflow focused on complex tasks that require real cognitive capacity.
2. Preventing employee burnout
Research shows that 70% of customer service agents report feeling overwhelmed. Long hours, the adoption of new technologies, increased contact volumes are some of the reasons that lead to agent burnout and eventually high attrition rates. This is a real issue which threatens performance and compromises the customer experience. Any customer service leader looking to impact their bottom line should be prioritising employee well-being and adopting strategies to prevent burnout. Enter AI and it’s multiple self-service applications that handle more basic, mundane, and repetitive customer requests allowing agents to free their minds and prevent downtime.
3. Utilize AI-powered agent training
AI also plays a vital role in agent training. If you are looking to impress your customers with superior service, you can train your support agents to be proactive by leveraging AI-powered technology that could test out multiple support scenarios and help agents practice appropriate responses. This motivates them to focus on high-value tasks and optimize support processes using their experiences.
Anticipate future events or trends/Personalization
Remember that old saying – History repeats itself? That is also true when it comes to customer care. AI can go through your customer service data, analyse it and identify patterns that enable you to anticipate events that are bound to happen or trends that are likely to emerge. In terms of effective, pre-emptive, and proactive support that knowledge is invaluable as it will allow you to plan ahead and deliver exceptional service.
AI can help with your personalisation efforts as well. Predictive analytics can foresee customer preferences and nudge them about anything that requires their attention. For instance, streaming services (think Netflix) may suggest new, upcoming shows for the user to see based on their past viewing history.
Eliminate manual analysis of overwhelming customer data
Customer service is a huge pool full of data. When you have the capacity to process and analyse all that information you can unearth insights that can help
- improve the customer experience
- increase agent engagement
- pinpoint root cause of repeat issues
- redesign internal processes
- identify opportunities and risks
- pin down training and re-skilling needs
- paint an accurate picture of customer expectations
The list above can go on and on and on.
Manual analysis of this data is not really a viable option. Thankfully AI can relieve you of that burden, go through your data and automatically deliver accurate insights to empower data-driven decision making.
Offer consistency across multiple platforms
Today’s brands must maintain a presence on digital and physical platforms and are faced with the issue of collating loads of data from several customers across different channels.
AI helps you achieve multi-channel consistency across your platforms as you can now collect and process data from numerous sources without a hassle. This way, your interactions with customers remain ever consistent.
AI in customer service comes highly recommended as a battle-tested tool. We’ve listed several use cases — all of which have the capacity to transform your contact center into a well-oiled machine. In a turbo-charged world, think of AI as an ‘extra hand’ on the field to augment the efforts of your team; so much so that you’d be doing your brand a disservice if you overlook it.
While the initial implementation budget may be significant, the overall impact on customer happiness — and, thus, your bottom line — makes AI a net positive in the long run.