What is good customer service and why do you need it?
Poor customer service costs businesses over $75 billion a year
Good customer service is table stakes for any successful business. Providing great customer service (including great customer support) ensures your new customers will keep coming back, and it deepens their relationship with your brand, service, or product. And outstanding customer service is a significant driver of word of mouth.
Customers remember two kinds of customer service: bad and excellent. A bad experience is typified by single-channel solutions, generic options, unfriendly or aloof agents, long wait times, and unreasonable transfers. Bad customer service is memorable, and frustrated customers are empowered to seek results by any means, including posting their issues publicly on social media. A poor customer experience costs businesses over $75 billion a year. But that’s not all. Research shows that 91% of unsatisfied customers will entirely part ways with a brand, and 78% will back out of a purchase, if the customer service is bad.
On the other hand, good customer service must be exceptional to elicit passion and word of mouth from happy customers. To get as close to excellence as possible, some businesses are looking to virtual agents and AI solutions to enhance their customer service efforts. By the end of 2021, Gartner predicts that companies will be spending $3.5 billion on virtual personal assistants.
What is good customer service?
Quality customer service has three aspects to it. It’s timely, it’s attentive, and it’s calm. In this era of customer empowerment, with new technological advances, customers and brands are in constant communication 24/7, 365 days a year. Therefore, organizations must be ready to assist customers in real time and satisfy all three aspects of good customer service.
To reach excellence, your customer service experience must be intuitive, frictionless, and nearly invisible in certain areas, but it must be defining and memorable in direct and personal interactions. When a customer reaches out to solve an issue, good customer service is welcoming and available on any channel. The doors are open, and a curated experience is waiting to lead them to a swift resolution through any device at any time. If they have asked for help before, they’ll expect to be remembered, and if this is the first time, they should feel expected. By the end of the session, your agent will solve their problem, and they’ll feel seen and appreciated by your business. The bottom line? Great customer service means being proactive and predictive wherever possible.
For an organization to meet those stakes, there are a few options. The traditional approach is to staff a massive customer experience center with enough highly skilled customer service representatives to give fast and upbeat service around the clock. But humans make mistakes, humans get overwhelmed, humans must take time to research what they don’t know, and humans are expensive.
Many organizations today find the cost of staffing a center full of live customer service reps too significant an overhead, so they’ve adopted a hybrid approach. They use live agents for tasks requiring a personal touch or higher cognition, while allowing virtual agents powered with artificial intelligence to tackle more routine and repetitive scenarios.
It pays not to get virtual assistants and chatbots confused. The primary difference between a chatbot and a virtual assistant is that the assistant can learn. A chatbot can be a handy tool, but its real value is providing very specific information derived from specific sources, information that will not change often: a business’s hours of operation or information covered in an FAQ. An assistant works with customers to quickly resolve their issues, it integrates with the company’s CRM system in order to automate requests, and it goes the extra mile to provide the best customer service.
Virtual assistants drive customer satisfaction
99% of organizations using AI-based virtual agent technology report an increase in customer satisfaction, according to a recent IBM Institute for Business Value study. A hybrid approach gives an enterprise business the best chance at effectively hitting all aspects of good customer service without incurring the high overhead costs associated with a live customer service team. Virtual assistants can be trained to answer questions immediately and provide the exact information the customer needs automatically. AI-based virtual agents can best represent your brand, remember previous interactions with customers, and draw from your existing data for predictive insights into best resolving an issue. If the virtual agent cannot answer the query, it can route the call directly to a live agent. In short, AI virtual agents provide solutions, not frustration.
Virtual assistants give your enterprise a customer-focused first line of defense that you can easily customize to fit various business needs. For example, in a customer self-service use case, you can serve your customers better than ever by allowing them to help themselves. Your virtual assistant can use your structured and unstructured data to answer more than just frequently asked questions by searching across your organization for the exact information your customers need. Another widespread use case is to set up a virtual agent to assist your human agents. With AI-powered search and predictive insights, an agent-assist use case saves your employees a lot of wasted effort. Both use cases are proven to exceed customer expectations and reduce response times.
Virtual assistants use natural language recognition to understand what the user is asking. Then they use AI tools like machine learning to discern what the user is trying to accomplish. The AI elements embedded in the assistant help it develop an increasingly granular knowledge base of questions and responses based on user interactions, improving the assistant’s ability to predict user needs accurately. For example, if a user asks about tomorrow’s weather, a simple chatbot can respond plainly with temperature and chance of precipitation. But a virtual assistant might understand the real thing the user needs to know: whether to bring an umbrella. Good customer service means respecting your customers’ time and proactively resolving customer issues.
Watson Assistant is the virtual agent that solves customer problems the first time across any channel. Built with good customer service in mind, Watson Assistant can be trained on your data to deliver a personalized, curated experience, providing your customer with a path of least resistance to resolve their issues. Watson Assistant’s simplified tooling makes it easy to get started on digital and phone channels. It also offers advanced capabilities like intent recommendations, disambiguation, and conflict resolution to reinforce effective customer service and drive customer loyalty.
Watson Assistant can be integrated with CRM systems and easily be trained to help customers reschedule appointments, track shipments, and check their account balance. It can also remember previous interactions and will automatically surface information based on those interactions. It also uses follow-up questions to understand better what the customer’s intent is. If Watson Assistant cannot help, it will automatically pass the customer off to a human agent.
Watson Assistant’s best-in-class natural language processing understands colloquial speech patterns to better engage with your customers, however they speak, and it supports over 12 languages.
Benefits at a glance
- A Forrester TEI report estimates a 337% payback in ROI over three years, and 100% payback in under six months. The same report finds a 30-40% reduction in operating costs and a 20% increase in workflow efficiency.
- Proven to be more accurate than competitive solutions by 14.7%.
- Handles thousands of concurrent phone calls to scale, supporting even the most demanding call center environments.
Now that you have a clearer picture of how AI can help you serve your customers and employees better, it’s time to take the next step.