ChannelVision Magazine

formal feedback process around customer experience.” In many ways, what we are seeing in the contact center space mirrors what is happening in data centers, marketing and sales de- partments: Companies are shifting away from stagnant, legacy-based systems and processes in favor of agile, responsive strategies. Massive Opportunity The reality is that many busi- nesses are far behind in their cus- tomer service efforts. Of the four potential categories that Liveops outlined for contact centers today (optimized, mature, developing and traditional), the vast majority fall into the least-two sophisticated catego- ries: Traditional (23 percent) and developing (46 percent). For agents, the goal should be to get all customers into the optimized category, where workforce is viewed as a competitive advantage and strategy is baked in to enable con- tinuous improvement. There is a tremendous oppor- tunity at hand for agents that can identify businesses that fall into the lower tiers and help them improve their efforts. Technologies to know To capitalize on this opportu- nity, it will require having a working knowledge of the latest available technologies. Here are some of the smart tools that companies are working into their contact centers: Artificial intelligence: AI is the driving force behind many of the contact center technologies that we see today, from interac- tive voice response systems (IVRs) to chatbots. In a contact center setting, AI can be used for natural language processing or the ability for a computer to understand human language in real time, and make mechanical decisions to complete basic tasks. Natural language processing is often used in voice- based identity verification systems and IVRs. Then there’s machine learning, which involves feeding computers large amounts of data, so they can “learn” how to better handle cus- tomer inquiries. Machine learning algorithms are being used in contact centers today to perform smart call routing, to reduce the amount of time that it takes for customers to reach the right agents. Another form of AI is sentiment analysis, or the process of scan- ning customer chats, voice and email interactions to read emo- tions. This type of software can help a business understand how customers are reacting to certain programs and initiatives. According to Oracle, eight out of 10 businesses have already in- tegrated or are planning to adopt AI as a customer service solution by 2020. The technology is rapidly improving, and it’s becoming more affordable for mid- to small-sized enterprises. at your service: Xaas July - August, 2018 | Channel Vision 37

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