Customer experience is the new imperative. The statistics are convincing: a Walker study reported that by 2020, customer experience will overtake price and product as the key brand differentiator. According to PwC, 65% of customers say that a positive experience with a brand is more influential than great advertising. And 86% of customers say a great customer experience makes them likely to use the same company again.
But for your customers to enjoy their experiences, you need to understand them and use that knowledge to deliver personalized experiences across the entire customer journey. This will encourage and incentivize your customers’ loyalty. The use of artificial intelligence (AI), bots, automation and machine learning (ML) in contact centers can make all this possible.
Contact centers generate huge amounts of data from customer contact via multiple channels, and proper analysis of that data helps you better understand your customers’ behavior and needs. You can then tailor a personalized approach to your customer service. This comes from ascertaining what questions your customers ask most for example, or identifying recurring issues that customers contact you about.
The right tools to do it
Artificial intelligence (AI), data analytics tools and automation all can play a role in the next-generation contact center operation. AI can be used to power predictive routing that replaces the old call queuing system with a tool that pairs customers directly with agents based on the customer’s individual characteristics and history plus an analytical assessment of the agent’s profile.
Predictive routing replaces the static, siloed queue approach with something that enables a wider-reaching, real-time omnichannel experience that comprises the whole customer journey: it adapts to changing patterns of interactions, builds up predictive models using continuous learning and dynamically establishes the required parameters for call coverage and prioritization.
AI also enables chatbots that can offer personalized self service for voice and digital channels, which makes customers happier and lowers your own costs. Using machine learning (ML) and natural language processing (NLP), a chatbot can understand the intent in customer requests, have access to a customer’s entire conversation history when it interacts with them, and respond to the customer’s questions in a natural, human way. Self-service engagements of this type cost 25 to 75 times less per transaction than human agent interactions.
ML also lets you define customer and agent attributes to improve your contact center offering and drive successful business outcomes. For example, you can look at patterns of improved sales figures and use them to adjust best practices and develop better training across your company.
Combining AI with human agents is another successful approach that lets you maximize the benefits of both. According to Forrester, companies that have mixed the two have reported a 61% improvement in customer satisfaction and a 69% improvement in agent satisfaction.
It’s about being able to tell the future
Analysis creates insights that enable you to predict what customers will want and expect – and even to pre-empt them. Accenture found that 89% of customers get frustrated because they have to repeat their issues to multiple representatives, so being able to know what customers want ahead of time is a powerful customer experience tool. AI, analytics and automation can help you give customers that experience – using predictive engagement.
Predictive engagement tools, like those offered by Genesys Altocloud, empower you to understand what your customers are thinking ahead of time. This allows you to engage with them when they want, where they want and how they want – even before they contact you. Analytics can show you, for example, that customers who had problem X also tended to experience problem Y. Using predictive engagement means you can prompt and check for problem Y in the same interaction, reducing repeat calls to your contact center, improving your first contact resolution (FCR) rates and improving overall customer satisfaction.
The best customer service is pre-emptive and is about knowing what your customers are thinking. Predictive analytics and engagement are about predicting customer behavior, anticipating when you need to offer agent support to customers browsing your site and enhancing overall customer experience by identifying and engaging with prospects and customers at the right times and via the right channels. Some 67% of customers give bad experience as their reason for churn, but only 1 out of 26 unhappy customers actually complain. The rest just leave. So, a good customer experience is vital in reducing churn.
Contact centers today can drive those transformative customer experiences for companies and customers. The right AI, analytics and automation tools will be central to that.
For more information, watch our video on creating AI-powered journeys for employees and customers alike.
For more than 20 years, Stéphane More-Chevalier has been working on improving companies’ customer relationships through diverse project management and product development. He led the implementation of contact centers on customer sites all over the world, including IT integration. With data intelligence and AI gaining ground, he’s now committed to strengthening the Orange Business Services portfolio developing AI-powered services on top of contact centers to create value for both companies and customers.