Forrester Vice President and Principal Analyst Kate Leggett blogged the emergence of what she calls "digital-first customer service solutions." These types of solutions are characterized as delivering automated interactions over digital channels. She contrasts these with what she calls traditional customer service solutions that offer workflow-based inquiries, case management, and guidance for customer service agents. Diverse sales models and the changing needs of both customers and the business means most companies will find themselves adopting a mix of both. And while these solutions might seem different, they share a key similarity: a dependence on workflow and automation, some of the fundamental building blocks in digital transformation.
Over the years, the role of the customer support agent has evolved from simply handling customer inquiries to building customer relationships and growing the business. According to the Salesforce State of Service Report, 71 percent of agents see their role as more strategic than two years ago. This means not only are agents spending more time solving complex issues, but they're also expected to upsell, cross-sell, and provide voice of the customer input into product development. The problem is, they're being asked to take on these changing responsibilities using the same old processes and tools. "As agents become more strategic, they have the potential to add more business value, especially in the area of customer experience," said Alok Ramsisaria, CEO of Grazitti Interactive, SearchUnify's parent company based in Sunnyvale, CA. "Having successfully completed hundreds of service implementations for enterprises all over the world, I can confidently say that the key to empowering agents is to arm them with contextual knowledge about the problem they're solving. And do it in a way that's scalable and delivers consistent results. Unfortunately, support teams are being hampered by manual processes and technology silos that keep them from servicing customers in the most efficient, effective way."
Enabling organizations to capture, share, and apply the collective experience and know-how of their people is seen as fundamental to competing in the knowledge economy. As a result, there has been a wave of enthusiasm and activity centered on knowledge management. To make progress in this area, issues of technology, process, people, and content must be addressed. In this article, we develop a road map for knowledge management. It begins with an assessment of the current state of the practice, using examples drawn from our experience at Schlumberger. It then sketches the possible evolution of technology and practice over a 10-year period. Along the way, we highlight ways in which AI technology, present and future, can be applied in knowledge management systems.
Enabling organizations to capture, share, and apply the collective experience and know-how of their people is seen as fundamental to competing in the knowledge economy. As a result, there has been a wave of enthusiasm and activity centered on knowledge management. To make progress in this area, issues of technology, process, people, and content must be addressed. In this article, we develop a road map for knowledge management. It begins with an assessment of the current state of the practice, using examples drawn from our experience at Schlumberger.
Kustomer, the SaaS platform that is reimagining enterprise customer service, introduced KustomerIQ, embedding Artificial Intelligence and Machine Learning across the Kustomer platform to enhance the customer service experience of companies competing in today's on-demand world. KustomerIQ uniquely integrates Machine Learning models and other advanced AI capabilities with the Kustomer platform's powerful data, workflow, and rules engines to enable companies to provide smarter, automated customer experiences that are more personalized, efficient, and effortless. The Kustomer platform stands out among customer service solutions for the comprehensiveness of available customer data and its business process automation that is driven by branchable, multi-step workflows and custom business logic. Read More: #5FutureStates Of Content Are Here: SDL's 2018 Content Predictions Come To Fruition "In today's crowded market, excellent customer service is often the differentiator that builds loyalty and trust between one brand to another," said Brad Birnbaum, Co-Founder and CEO of Kustomer. "With KustomerIQ and the inclusion of Artificial Intelligence and Machine Learning into our omnichannel platform, Kustomer will now go even further in helping brands automate their business processes, while making it easier for their agents to take action on customer information, ultimately developing a stronger and more profitable customer relationship."