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A Definition of a Self-Learning Knowledge Base
A self-learning knowledge base is often found to be a key component of enterprise level self-service solutions. Leading knowledge base technologies use machine learning algorithms to automatically collect customer queries, learn from representatives’ responses, and continuously expand the knowledge base over time.
As its name might suggest, the self-learning knowledge base continues to improve in accuracy and performance as it receives additional information. Knowledge Base systems which are integrated with digital self-service solutions improve with each customer interaction that occurs through the self-service interface. The machine-learning algorithms which are found in more advanced knowledge base systems are usually designed to evaluate and process large amounts of data received through customer interactions. This big data provides deep and valuable insights into customer needs and trends within the digital experience.
Benefits of a Self-Learning Knowledge Base
The goal of combining a self-learning knowledge base with a self-service solution is to deliver an optimal customer service experience that provides a personalized and detail-oriented response to each customer. By ensuring that relevant knowledge is put in front of customers every time they seek support, it’s possible to reduce the rates of website abandonment, lower support costs, and increase efficiency throughout the customer experience. Moreover, sophisticated solutions can learn nearly all of an organization’s business questions within the first three months of deployment, making implementation a fairly quick and easy process for any organization.
The quick learning capabilities that are typical of a self-learning knowledge base can often address an organization’s goal of helping to reduce customer service agents’ overall workload. In most support centers, agents can easily find themselves flooded with routine questions and email queries on a daily basis. With an effective system in place, oft-repeated responses become learned and this information becomes readily available to customers, reducing the need for agents to respond to repetitive queries. This decreases the burden on customer service agents, allowing them more time to handle user-specific support issues that typically require deeper insight and understanding. Ultimately, this enables the organization to meet several business goals, including increased customer satisfaction, cost reductions, and greater productivity and improved efficiency among the support agent team.
Specific benefits of a self-learning knowledge base include
- Improved customer experiences, where customers have access to the most relevant and timely information.
- Reduced contact center costs and overhead as a result of streamlined customer service delivery.
- Improved efficiency of customer service operations.
- Improved ROI due to reduced shopping cart abandonment.
- Intuitive capabilities that help customers quickly solve problems on their own, resulting in higher levels of customer satisfaction.
- An increase in time for staff to handle other support issues, because the knowledge base answers customers’ basic service needs.
- More informed customers and communities.
- Increased search engine visibility for self-learning knowledge bases with search engine optimization capabilities. This also helps to ensure that online information is easily discoverable for customers.
- Enhanced support staff skills and job satisfaction, as customer service representatives spend time responding to more challenging questions while the self-service platform handles support questions of a more basic nature.
Self-Learning Knowledge Bases are the Future of Customer Service
Steven Van Belleghem, of Fast Company, conducted a global survey in collaboration with SSI and No Problem! to determine the percentage of customers who prefer self-service solutions. The survey found that “the majority of consumers favor a self-service solution, including the safety net of personal contact if the consumer so chooses. This trend is even more apparent in countries like China, Brazil, and Singapore than is the case in Europe or the U.S.” As consumers become accustomed to having information at the tip of their fingers and at lightning-fast speed, they expect companies to deliver service in much the same way.
The implications of the study are that customers expect companies to improve their service levels and deliver answers and solutions in a timely, efficient way; this also means customers do not want to have to contact companies more than once. In fact, Van Belleghem’s study determined that 39% of consumers expect email replies in fewer than 24 hours, while Twitter and Facebook users expect an answer in fewer than 4 hours.
More important, Van Belleghem’s study determined that self-service is the only long-term solution already meeting customer expectations. 70% of consumers expect a self-service option for handling questions and complaints. Van Belleghem urges companies to keep in mind, however, that personal contact as a safety net is critical as a safety net if self-service should fall short.
It’s clear that companies desiring to meet customer demands now and in the future must adapt with modern tools to provide seamless experiences and easy access to important information. The customers have spoken, and it appears as though sophisticated self-learning knowledge bases are the future of customer service.
