As its name suggests, digital transformation is changing how companies operate—and the contact center is among the most measurable areas for success. A big part of this effort revolves around artificial intelligence, which can dramatically improve the customer experience by automating mundane processes and applying context and cognition to more complex interactions. This ensures customers get the information they need quickly and accurately, and it helps agents deliver maximum value whenever and wherever they engage with customers.
Better still, AI can dramatically improve the key performance indicators (KPIs) on which contact centers are measured. This includes everything from the time it takes for a contact to be handled (first-response times, abandonment rates, blocked calls, time on hold, etc.) to call quality and efficiency (service levels, first-call resolution) to customer and agent satisfaction. Intelligent self-service helps companies handle more contacts more quickly, while data-driven analytics ensure agents can offer a more effective and satisfactory experience.
In short, AI can transform the metrics that matter most to you and your contact center: call deflection, FCR, agent productivity, agent attrition and even CSAT, NPS and CLTV.
AI in the contact center isn’t the stuff of sci-fi; machines will not replace humans any time soon, if ever. Instead, the objective for leading companies that are deploying AI is to augment and enhance experiences for customers and agents. Artificial intelligence enhances the customer support experience through natural language processing (which makes it possible for computers to understand actual human speech; think of it as the voice recognition you always wanted) and machine learning (which enables applications to continuously improve their programming based on real-world interactions and data). Exponential, practical advances in AI solutions that are integrated into the customer record and interaction history allow the system to interact with your customer data and provide “intelligent,” contextually relevant self and agent-assisted service.
Many companies initially use AI to automate the simple, repetitive processes that are the backbone of any contact center. AI helps companies manage those tasks more intelligently by using historical and real-time information to contextualize every interaction. More importantly, even during human-driven interactions, AI can handle the mundane tasks that are required during every exchange, such as collecting contact information and incorporating data related to the problem at hand. It can then pass that information along to agents, who can approach the customer with knowledge instead of basic questions. Not only does this position the agent to jump right in with advanced help, but it also appeases the customer, who is tired of constantly having to repeat the same information on customer service calls.
Regardless of channel (voice, chat, SMS, social), the agent can then leverage that information to deliver a more personalized and complete experience. For example, AI can give the agent relevant data about the customer’s history with the company, as well as any steps the agent has taken to resolve this particular issue (including self service). That can help the agent resolve the problem at hand and develop a deeper and more personal relationship with the customer, and even turn a negative experience into a positive one.
Artificial intelligence can also help contact centers be more proactive, allowing agents and bots to anticipate customers’ needs—sometimes before even the customers realize they exist. AI can recognize that a high-value customer is searching a self-help site and offer live assistance earlier than it might in other situations. AI can also analyze incoming contacts to determine how important they are and then move them up in the queue accordingly. Once contact has been made, AI can help agents by searching databases, GPS and any other relevant information sources to contextualize the interaction—say, by letting the agent know that the customer’s phone service is, in fact, being repaired. It can even use historical data to anticipate when a customer might need service and support and reach out ahead of time with an offer, saving the customer from making the effort and lowering costs for both parties in the process.
AI can also help managers improve the customer experience going forward, based on real-world information. By recording calls and running them through a language processor with AI capabilities, companies can learn not just what was said and done, but also whether the customer was likely to be satisfied and is a good candidate for a follow-up contact or up-selling, and where room for improvement lies.