Customer service is a people-focused business, and according to the Harvard Business Review, there are elements of service that are hard to automate.
But there is great value that businesses can realize by enabling artificial intelligence (AI) to automate portions of their service organization. Specifically, intelligent chatbots can extend customer relationship management (CRM) software to deliver better customer service than another human at the end of a phone or internet connection. We still need to allow human workers to focus on personalized service, solving complex problems and escalations and use AI to handle more routine tasks. Customer Service Week is a great time to consider the impact of AI on customer interaction and satisfaction.
AI, chatbots and great customer service
People matter in customer service. Unfortunately, companies have a fixed number of customer service representatives and a fluctuating volume of inbound requests for service. And requests may come in from multiple channels—phone, chat, social media, email. That results in the long hold times and disjointed communication. So even once a human agent does connect with the customer, they often have only incomplete information.
Today, AI solutions that unite chatbots with 21st Century multi-channel CRM software can solve both these problems. This software can learn which answers posed in a chat are appropriate for each question and automate a significant majority of chat interactions. A chatbot can be taught to answer commonly-encountered questions, like inquiries about when a technician is scheduled to arrive. Of course, at some point, the AI chatbot may get stuck when personalized service is required, and a human agent takes over the discussion thread without missing a beat. This should be seamless not only to the customer, but for the internal customer service, ticketing and support systems as well. The chatbot—regardless of whether driven at a given moment by AI or a human agent—should update the same customer record as other channels including social media, phone and email.
Machine learning for customer service
Advanced AI functionality can actually learn from answers provided by human agents and get better and better at answering questions through machine learning processes. The chatbot should also seamlessly hand off the chat to a human agent when the extent of its learning is overtaken. Only then can the entire customer experience be unified and consistent, even with a static number of agents handling a rapidly growing of fluctuating volume of customer interactions.
AI-based chatbots for instance can enable a good agent to handle up to five or more chats at a time. It can capture Facebook messages and Tweets and direct them to an agent or to AI for intervention. AI alone can handle, typically, between 50 and 60 percent of requests, freeing up human capacity or lowering staffing levels required to handle a given volume of activity.
AI can deliver better service when it has access to extensive information about each customer. So full integration with enterprise resource planning (ERP), field service management and other enterprise tools is essential. The key is let AI work with more rather than less information on the status of the customer’s account, including their maintenance or service history and warranty or service level agreement entitlements.
Conclusion
Service organizations should recognize the tremendous potential AI holds—they can harness it to transform their operations, outflank their competitor and disrupt their markets. We are only starting to tap into the different ways AI can be used to better solve the problem of delivering optimal service in a rapidly changing environment as adoption is still lagging despite the real benefits AI brings. The good news is there are several straightforward and easily accessible ways service executives can harness AI technology right now, today.
To learn more about how AI can improve the field service customer experience, download our new whitepaper, Three Practical Artificial Intelligence (AI) Approaches for Field Service Management.
