GOODBYE DOCUMENTS , HELLO SNIPPETS , CHUNKS
The concept of the document has historically served as a fundamental building block in both the analog and digital realms , often taken for granted and unquestioned .
However , the transition from analog to digital merely transposed this concept into a new form without adequately considering the substantial disparities in capabilities , formats , and delivery mechanisms between the two worlds .
A prime example of this disconnect can be observed in Google ' s evolution from presenting full documents or web pages in search results to providing succinct snippets that directly address users ' queries . It ' s safe to say that few , if any , users actively desire lengthy walls of text in their search results , a sentiment shared by customers seeking swift and relevant answers .
Consequently , the future of KM demands a harmonization of the final delivery format with the structure and format initially used for content creation and storage .
While some KM software has already made strides in this direction , there remains a significant journey ahead . Presenting customers with mere links to webpages , copy-paste FAQ responses , or cumbersome blocks of text represents suboptimal CX .
Today ' s users expect quick and precise solutions to their queries , having often conducted preliminary research . A response that merely redirects them elsewhere falls short of the definition of a solution .
52 CONTACT CENTER PIPELINE
Similarly , providing contact center agents with extensive textual resources can impede their ability to efficiently resolve customer issues during phone calls or chats . This emphasizes the need for a more user-centric approach to knowledge delivery .
A NEW ERA OF KM SOLUTIONS
The current landscape of KM software primarily revolves around solutions centered on editorial and management functionalities , often offering limited capabilities for content delivery .
Additionally , these solutions often rely on outdated machine learning and AI technologies , which are not their primary foci or areas of expertise .
Consequently , the impending evolution of KM software is poised to disentangle the realms of management and delivery , likely necessitating the adoption of entirely distinct solutions for each facet .
On the delivery side , there is a burgeoning trend referred to as “ Knowledge AI ,” wherein vendors leverage a combination of NLU , LLMs , and vectorization , as discussed earlier , to substantially outperform conventional methods .
But while these cutting-edge delivery technologies show promise , they currently lack the critical management capabilities crucial for ensuring the accuracy , quality , and usability of knowledge resources , as previously highlighted .
This growing disparity underscores the need for a reevaluation of KM strategies , as the technological advancements on the delivery side have surged far ahead of their managerial counterparts , warranting the development of new solutions ( Knowledge AI ) to bridge this gap .
The trajectory is clear , signaling an inevitable shift toward more agile and specialized KM approaches .
BEST PRACTICES FOR CONTACT CENTERS
In this ever-evolving landscape of customer service , contact centers are increasingly turning to Knowledge AI and cutting-edge knowledge management solutions to enhance their operations . Leveraging these advanced technologies opens up a new era of possibilities , where customer interactions are more streamlined , efficient , and personalized .
To maximize the benefits of Knowledge AI , contact centers must adopt several best practices that ensure optimal utilization and seamless integration of these innovative tools .
Holistic Integration
• Comprehensive knowledge base . Develop and maintain a well-structured and up-to-date knowledge base that encompasses a wide range of topics and issues relevant to your products or services .
• Seamless integration . Implement Knowledge AI solutions that seamlessly integrate with your existing contact center infrastructure , including CRM systems , chatbots , and agent interfaces .
• Multichannel accessibility . Ensure that knowledge resources are accessible across all customer touchpoints , such as websites , mobile apps , social media , and live chat , to provide a consistent CX .
... CONTACT CENTERS ARE INCREASINGLY TURNING TO KNOWLEDGE AI ...
User-Centric Approach
• Contextual understanding . Utilize NLU capabilities to comprehend user queries , considering context , intent , and sentiment , enabling the delivery of personalized responses .
• Dynamic content delivery . Employ Knowledge AI to dynamically tailor responses based on user needs , preferences , and interaction history , offering the most relevant and concise information .
• Self-service optimization . Encourage self-service by empowering customers with easy-to-navigate knowledge resources , reducing the need for agent assistance and enhancing customer satisfaction .