Chatbots have become practically synonymous with artificial intelligence (AI) for customer service. The chatbots that leverage AI and machine learning (ML) can augment a customer service team’s capabilities by answering routine questions, providing 24/7 access to information, enabling multilingual support, and enhancing overall customer experiences.
But the options to use AI for customer service extend far beyond a typical chatbot. Businesses can implement AI-powered technology in many other ways throughout their customer service operations, helping to evolve good customer service into great customer service.
How is AI used in customer service?
AI-powered customer service can benefit every aspect of an operation, from delivering exceptional user experiences for customers and agents to creating more cost-effective, efficient workflows. Although it’s easy to think AI might take over human jobs completely, it, along with machine learning, can actually improve your customer experience by freeing up time for humans to work on more important tasks.
Examples of AI in customer service
Below are examples of how customer service support can benefit from using AI.
Big data analysis
AI and ML can analyse large data streams in a short period — much faster than any human could. Furthermore, these technologies can identify patterns, trends, and anomalies that may go undetected by people overwhelmed with the sheer volume of data that a customer service or contact center generates. But with AI for customer service, agents can increase productivity, eliminate duplicated effort, and control costs.
AI and machine learning can directly help agents do their jobs more effectively. For example, AI can analyse customer service interactions, quickly find the information customer support agents need to resolve issues and display them on their computer screens.
This application of AI for customer service saves time, enabling agents to resolve customer queries faster. However, it also helps agents, particularly new agents, do their jobs more competently and with less stress.
Conversational analytics uses natural language processing (NLP) to capture data from human-to-human conversations. This technology provides greater insights into customers’ impressions of your brand and their level of satisfaction. It can also help evaluate agent performance and pinpoint areas where your agents may need retraining.
Robotic process automation (RPA)
In addition to providing agents with quick access to the information they need during customer interactions, AI can actually handle some tasks that take up an agent’s time. AI-powered robotic process automation can perform simple tasks, like updating records or generating follow-ups so that human agents can move on to the next call.
A Deloitte survey found that organisations implementing RPA saw ROI in less than 12 months, with an average of 20% of a full-time equivalent capacity provided by the solution. Additionally, 90% of companies using RPA see improved quality and accuracy, 86% report improved productivity, and 59% report cost reduction.
Successfully training new customer service agents is key if you’re wondering how to provide the best CX. However, it is traditionally a time-consuming process — and there’s always a concern that the agent’s first call will be an unusual customer query. AI can create a training program using speech-to-text capabilities, run new agents through test scenarios based on FAQs, and assess their readiness to begin to work independently.
The self-service trend is growing. About 71% of customers want companies to offer support over messaging rather than only via phone.
Although a knowledge base can give customers a self-service option to some degree, AI can intelligently help customers resolve issues on their own. ML and AI can sense human behaviour patterns and learn the best ways for customers to find the necessary answers.
How does AI help with customer satisfaction?
While artificial intelligence and machine learning can optimise processes, keep in mind that AI for customer service can also enhance experiences — sometimes much more than human agents using traditional processes alone. For example, AI for customer service can do the following.
Personalise user experiences
AI can analyse data quickly and tailor responses to individual customers. For example, with AI, customer service can consider a customer’s location and make offers for products or services available locally. AI can also analyse an individual customer’s data for an even greater degree of personalisation.
Improve human interactions with customers
AI for customer service also helps human customer service representatives do their jobs more effectively. AI can collect information from a handoff to agents for faster issue resolution. Furthermore, when AI chatbots handle basic queries, agents can focus on more complex matters and provide excellent customer service experiences.
How does AI help support agent satisfaction?
AI for customer service also benefits agents, helping to set them up for success and create a less stressful work environment. AI for customer service can accomplish the following.
When customer service agents have a long queue of customers waiting for their assistance and a ticking clock that records their resolution time, their job can be stressful. And too many stressful hours lead to burnout. AI can give customers self-service options shortening queues and helping to avoid agent burnout.
When AI automates tasks and provides agents quick access to the information they need, each interaction is faster and more efficient. Customers appreciate the short wait time, and agents appreciate quick resolve.
Is AI the future of customer service?
AI brings many benefits to customer service, ultimately increasing efficiency and productivity and improving customer experiences. With 57% of U.S. consumers saying they’d tell a friend to avoid a business after a negative experience, AI-powered customer service that provides positive interactions could become a factor in competitiveness. As a result, businesses will likely take advantage of AI customer service for benefits like the following.
Cost reduction and resource optimisation
AI implementations save time, enable self-service, and reduce the demand for agents to work overtime, all while providing excellent customer service. Additionally, scaling customer service capabilities with AI technology is more cost-effective than hiring new agents — and if demand decreases due to an economic downturn, a business can scale back AI and avoid the need to lay off employees.
When customers have questions or need assistance, they don’t want to wait for business hours. AI can work around the clock and be accessible via phone calls, website chatbots, social media, or apps like Facebook Messenger. Customers can get the answers when it’s most convenient for them — and AI for customer service helps agents avoid a 9 a.m. spike in volume.
Businesses use AI and ML to understand how things are now — the project’s current status, guidance through a process, and where items are in manufacturing or shipping. But beyond descriptive analytics, AI and ML can also provide predictive insights and should be part of your overall CX strategy. For example, AI can mine data to generate leads for the sales team, analyse interactions for signs the customer may churn without intervention, and provide business leaders with probable outcomes for intelligent decision-making.
The customer service team can shift its focus from reactive to proactive with AI. In fact, AI can provide insights into the information customers may need based on the products they’ve purchased or the services they’ve received.
Waiting for customers to contact the customer support team won’t be necessary. The team can initiate and control interactions and ensure great customer experiences.
Consumers are familiar with AI-powered virtual assistants, which answer their questions and help them perform simple tasks. As AI platforms’ capabilities expand, virtual assistants can guide customers through decision-making to help them make purchases they’ll be most happy with, make decisions about repair vs. replacement, or choose the best service offering for their needs.
Is AI in customer service expensive?
AI customer service platforms vary in price, but many are delivered through the Software as a Service (SaaS) model, charging a monthly fee rather than requiring businesses to make a CapEx.
Of course, each business needs to consider its budget and the pain points it plans to solve with AI. But remember to factor in the total cost of ownership for customer support and weigh the costs of the AI solution against other options, including hiring more employees. AI’s cost will likely compare favourably.
How to get started
Getting started with AI for customer service requires you to make some decisions. First, you need to determine the tasks that AI will perform for your business and the data you need to provide to train the platform, such as integration with your knowledge base or your customer service management system.
Working with the right AI customer service platform provider can make the process easier, providing the guidance and support you need for a successful implementation.
How Zoom Virtual Agent can help
Zoom Virtual Agent provides various options for using AI for customer service, from agent assistance and data analysis to AI chatbots. You can scale more efficiently while never compromising on delivering excellent CX. Zoom Virtual Agent also integrates with various CRM and CCaaS platforms to help you create an intelligent, connected unified communications environment.
Contact an expert today to explore the range of ways AI can benefit your customer service operation.