Artificial Intelligence (AI) offers tremendous competitive advantage to early enterprise adopters who seek to augment human interaction with their customers.
Gartner predicts that 89% of businesses will depend on customer experience to be their primary differentiator in 2017. Faced with increased commoditization of products and services, organizations are focusing their attention on creating innovative ways to provide personalized customer experiences.
In recent years, efforts to provide technology innovation in customer engagement have focused on self-service channels. Organizations are deploying smarter IVR systems, chat bots, consumer applications and portals with AI and machine learning concepts. We know that customers are increasingly adept in managing these customer-facing systems and that there is a growing preference for self-service. However, there are still instances where a customer prefers human interaction. An opportunity exists to capitalize on this preference by providing tools that augment the capabilities of frontline employees in human-assisted channels (i.e. call center, retail and field environments).
In order for organizations to transform their human-assisted customer engagement channels, organizations must begin by dismantling data silos, unifying disparate systems and interfaces, and aligning operational structure. Too often human-assisted channels are infirmed by system limitations and/or process segmentation. Organizations must seek to integrate systems and align sales and service functions with a focus on providing a streamlined channel that supports single touch resolution. Additionally, organizations that possess the agility to iterate quickly, react to predictive analytics, and seek to thoroughly understand customer segments and stories will be best positioned to lead differentiation in customer experience.
Data-driven applications and platforms that unify workflows and leverage AI can make an significant difference to customer interactions within call center, retail and field environments. Take the example of a customer calling into a telecommunications provider to report that they are having picture quality issues on the new television that was bought to replace a stolen television. Through natural language processing and machine learning the application could analyze the call in real-time, understand the issue, offer resolution recommendations to the support representative, while also picking up on the opportunity for a cross-sell of home security products. In this case, AI is applied to augment the call center representative and engage both service and sales capacities to quickly diagnose an issue while also prompting an offer for additional services. Similarly, enterprises have an opportunity to apply AI concepts by providing prescriptive analytics and recommendations in cases where a human simply cannot process large data intensive correlations quickly enough to deliver the same decisioning.
Enterprise organizations should consider exploration into the application of AI within human-assisted customer engagement channels as it offers an opportunity to further differentiate from competitors.