Transform Customer Service With Next-Gen Knowledge: Why and How
The consumer has spoken.
Forrester Research asked 5,000 of them, “What created the biggest pain when you contacted a business for customer service?” They answered lack and consistency of agent knowledge, followed by the difficulty of finding relevant answers on company websites. So, what is driving this dissatisfaction?
Self-service and peer-to-peer service adoption continues to rise, with millennials leading that trend. Naturally, questions that come to agents are more complex.
Contact center training budgets are being cut by as much as 60%. With inadequate training, agents try to improvise with their answers, leading to repeat calls, compliance issues, and customer complaints.
Legacy knowledge management (KM) systems are not smart enough for the modern contact center. Many organizations confuse data, and document/content management systems with KM.
Channel-specific knowledge silos compound this problem, creating multiple “right” answers with frustrating results.
Knowledge-enabling customer service contact centers
Here are key attributes to look for in your KM system (and the solution provider).
Does it find?
Can the KM system find accurate answers fast when the customer is on the line and the pressure is on? Make sure your KM system makes findability easy with flexible search options so that the user can pick the path to the answer he/she likes. Examples of “find” paths are FAQ, keyword search, natural language search, federated search, topic tree browsing, etc.
Does it federate?
Sometimes, “power users” know more about products than even the companies that make them. Likewise, in purchase journeys, online reviews are often the first stop. Compiling answers from multiple sources and presenting them to customers while marking them as trusted/curated or otherwise is called “search federation,” an important KM requirement now. Likewise, the KM system should be able to “harvest” answers from such sources automatically and feed them to the knowledge manager for quality control and publishing as trusted knowledge.
Does it personalize?
One way to increase speed to answer is to get hyper-relevant right at the start by personalizing for customer preferences, agent roles, agent skills (e.g., based on products, functions such as servicing, selling, language skills, etc.), past history, etc. The system should be able to personalize for authenticated customers or even anonymous prospects wherever possible, while making it easy to deliver hyper-relevant knowledge from one single knowledge base (KB).
A financial services BPO serves multiple clients from a single eGain-powered KB. eGain Knowledge delivers personalized views for agents, depending on the clients they serve, the agents’ roles, and whether the caller is a consumer. Queries cover payment processes, credit card issuance and reissuance, fraudulent use, complaint resolution.