The contact centre glossary covers many of the most common vocabulary, measurements and technologies related to call centre software and customer experience.
AI Customer Service
Digital transformation is one of the hottest topics among CIOs of companies that have mandated improving the customer experience as their top priority. Slight improvements are no longer good enough. Businesses that recognize delivering extraordinary customer experiences is a key differentiator have started to completely rethink their approach. In doing so, they have quickly come to realize that artificial intelligence (AI) is critical to achieving this goal. According to Gartner, 55% of companies have started or plan to invest in AI by 2020.
Customer care today remains mostly reactive. Companies wait for a customer to call into the contact center. The agent asks a series of questions to gather information needed in order to answer the customer’s question or solve their problem. If the agent is unable to do so, they typically pass the customer on to another agent, which starts the whole process all over again. The customer usually must answer the same questions asked by the previous agent and end up frustrated and feeling like their time is being wasted. AI can eliminate this repetition.
AI processes massive amounts of data much faster than humans. It also extracts insights by identifying patterns in data and can use what is learned to predict behavior and outcomes. AI can even acquire emotional and social intelligence and consider them in decision making.
In regard to customer service intelligence, AI can take all the data from audio calls and their text transcripts, chats, email, social media, and video and nearly instantaneously process it to provide incredible and highly personalized customer experiences.
Let’s take a look at a typical airline customer’s experience (without AI) whose flight has been canceled due to weather. Jim decides to log onto the airline’s website to search for a new flight. All the flights to Heathrow are canceled or full. He expands his search to include Manchester and Gatwick Airports. After 30 minutes Jim gets frustrated and calls the airline. The agent asks for all the same information that Jim already entered online. Jim is worried that flights are filling up and is irritated by the further delay. After another half-hour, his flight is finally rebooked, but Jim is very dissatisfied with his experience.
Now let’s look at what Jim’s experience would be like if the agent had received guidance from AI. When the agent picks up Jim’s call, AI has gathered the necessary information and understands why Jim is calling. The agent says, “Good afternoon, Jim, thanks for your loyalty. Can I help you rebook your canceled flight?” The agent already knows the best alternatives and let's Jim know there is a flight available first thing in the morning to Gatwick. Jim books the flight and has a very satisfying experience.
In this second example, AI understood who was calling and what was needed. This allowed the agent to provide immediate options without having to look anything up. The agent was able to resolve the customer’s issue quickly. The customer is happy because they have had a great experience and the agent can move on to helping other customers.
Why AI is Essential To Exceptional Customer Service
AI is redefining the way customers interact with brands. Companies gather vast amounts of data on customers including account information, preferences and activities. The volume of data is typically housed in several different applications and cannot be efficiently processed and analyzed by humans. Machines powered by AI examine the data and provide insights to customer care agents faster and with greater accuracy than they could get on their own. This puts the right information at the agent’s fingertips at the right time. In the realm of exceptional customer care, AI is a game-changer.
Some companies have already begun to deliver AI-guided virtual assistants enhanced through natural language processing. Others use predictive models based on machine learning. With the help of AI, companies are able to improve many aspects of customer care including issue resolution, online experience, loyalty, and proactive preventive assistance. Proactive services mitigate abandonment and ultimately improve customer satisfaction. Industry experts predict that the majority of customer support will be conducted without a human agent.
Here are just a few of the many benefits of Artificial Intelligence in customer service:
- Provides 24/7 support
- Resolves customer issues, fast
- Reduces agent and customer effort
- Identifies customer behavior patterns
- Uncovers customer preferences
- Enables personalized experiences
- Provides proactive alerts
- Minimizes complaints and abandonment rate
- Saves training costs
- Improves customer satisfaction and retention
AI provides meaningful insights to improve and personalize engagement and customer experience. It can even predict what customers want and how they will engage with brands.
How AI Delivers On Its Promise
There are many ways that AI is delivering better customer care by employing machine learning (ML) and natural language processing (NLP). ML processes huge amounts of data and then learns from it. NLP processes and interprets both written and spoken messages. Utilizing these two capabilities, AI provides cognitive computing power to improve service efficiency and effectiveness.
Consumers are already interacting with AI technology to book flights and hotels, get travel tips and fashion tips, place food orders, and schedule doctor appointments. AI-assisted customer care can provide responses and even resolution to certain customer issues with greater accuracy and speed than humans can deliver on their own. A recent survey conducted by Tata indicates that nearly 32% of major companies currently use AI in customer care. AI can be deployed to provide customer support via email, chat, web portals and phones without any human intervention.
24/7 Self Service
Self-service options enable customers to solve issues on their own. This could be through accessing an online knowledge base, FAQs or tutorials. Or it could mean that customers interact with AI-powered virtual assistants to resolve an issue. So instead of talking to an agent, they can save time by communicating with voice or touch-tone inputs. According to a global survey, 67% indicated that they prefer self-service over speaking directly to an agent. Perhaps another reason that customers prefer virtual assistance is that it is available 24/7. So, if an issue arises after hours, they can get a resolution without having to wait until the following day.
Virtual assistants not only save time for the customer and can improve the customer experience, but they can also save money for the business. For one thing, virtual assistants can handle large volumes of interactions at once. This can significantly reduce the number of calls coming into the contact center, which can potentially lower staffing costs. As AI continues to evolve, virtual assistants will become an even more reliable and flexible must-have self-service choice for customer care.
AI Assisted Services
In addition to leveraging AI as a self-service option, AI can assist contact center agents to significantly reduce the time it takes to resolve customer issues. Machine learning and AI can comb through massive amounts of data in seconds to provide answers to agents almost instantaneously that can help them effectively address customer issues, questions, and complaints that AI-powered self-service cannot solve on its own.
Although many customers, particularly Millennials and Generation Xers, are happy to leverage virtual assistants for the first-level service, as soon as they run into a snag or need help with a more complex issue, they still prefer to talk to a person. But when they do get to an agent, they want the agent to have all the background information they need and understand their issue. That’s where AI can enhance agent decision-making to speed time to resolution.
By harnessing the power of AI, companies can uncover customer behavior patterns and tap into interaction history to develop detailed customer profiles and deliver personalized experiences. So, when a customer calls into a contact center, the agent can greet the customer by name, know if the customer is a loyalty program member, and have at least some idea of why they might be calling. Companies can also offer personalized recommendations. In addition to improving the customer experience, this level of service can boost engagement.
According to a study by Accenture, 44% of consumers surveyed said they were frustrated by companies that failed to deliver personalized experiences and 41% switched companies due to lack of personalization and trust. Using AI-augmented personalization can help improve every customer care interaction, which can influence customer satisfaction and repeat business.
Proactive and Predictive Service
More often than not, consumers prefer pre-emptive action from the brands they choose. Rather than waiting until they are personally affected by a known issue, they appreciate it when a company reaches out to them with an alert informing them of an issue they might experience. They also want to receive an explanation of the cause, the remedy, and when it will be fixed. Proactive contact builds trust and trust builds loyalty. Resolving service issues before they happen with proactive analytics can lower abandonment rates, reduce complaints and improve customer satisfaction.
AI can also use machine learning algorithms to predict what customers want based on their preferences, visited content and the choices they have made in the past. In addition, AI can suggest the most suitable response or next best action to agents while they are interacting with a customer. It can also respond independently from the agent with real-time offers of FAQs or links to a knowledge-base. In addition, AI and predictive analytics can indicate a customer’s likelihood of canceling a service or purchasing a product.