Using Knowledge Management to Simplify Complex Customer Queries


By Trey Norman

More complex customer queries call for knowledge management to simplify tasks. Simplifying the steps taken for answer retrieval is beneficial not only for companies and their employees but also for customers.

In addition to reducing time and cost, more benefits arise. With knowledge management technology, call center agents have it easier with access to all company data right at their fingertips every time a customer picks up the phone. The request often requires more details than someone confirming their account number or product delivery date, and complex queries send agents on an endless hunt for information.

Knowledge management turns complex queries into a simple and productive phone call between brand and customer.

Call center agents can look up relevant data in no time to help customers get the information they want. This diminishes the need to transfer them because the first person on the phone has a 360-degree view of company knowledge, allowing them to quickly find the data and keep the lines open for the next caller.

The Value of Search and a 360-Degree View

Considering a company and its data, so much comes to mind with the breadth of technology and applications used today. From emails, sales documentation, contracts, support tickets, chats on internal collaboration platforms, and marketing analytics, there is way too large of a scope for customer service agents to find what they need and keep a customer happy in a timely manner. Eventually, they may resolve the issue, but at what cost?

High-level knowledge management with the help of artificial intelligence can slash through data silos and connect prominent information from all relevant sources. All a company needs to do is make it accessible to employees on the front lines.

While search is a significant function of these systems, proactive input and graphical displays can also be essential within call centers. From a search standpoint, representatives can search for keywords related to the specific customer or the issue needing resolution. Generated are search results, like on Google or Bing, of resources and content about the topic—precisely filtered the way the agent needs it. Query results could lead to a support ticket of a past customer who called with the same problem, or it may lead to a helpful whitepaper that discusses the topic in question.

But there is more to solutions than just searching and finding. We all know this is not always how it goes, as many of us have been on page ten of google results before. Machine learning techniques like Natural Language Processing (NLP), understand written and spoken language. That said, queries will lead to the exact sentence of a whitepaper or support document because intelligent systems understand what the employee needs just as a human would.

Not All Answers Have a Single Source

Search and search only may not be what the company and customer need. With complex queries, it may be unlikely the full answer lies in a single document. Connecting data sources allows graphical overviews to be created from all relevant sources. On one display, past customer tickets can appear to agents while specific data about the customer is highlighted on another, right next to each other in one central location.

Customer service agents don’t need one source opened on their primary monitor, another open on a second monitor, and a third source hiding behind another window. They can relay information back to the customer on the other end from one place that shows every source.

Auto-Generated Responses: Answering Questions for Agents

The last part is where technology really amazes. Another popular machine learning technique used in knowledge management is NLQA, Natural Language Question Answering. Not only does NLQA understand human language the way NLP does, but it can auto-generate answers based on sources of information within the company. Many companies have turned to chatbots to reap the benefits of Natural Language Question Answering and automated assistance.

But why should a chatbot get all the cool and innovative tools when people are still picking up the phones and relying on humans to support them? Taking advantage of this could lead to support agents receiving answers in real-time based on the spoken words of the caller or typing in the query. This practice saves many hours and dollars while making a difficult job more manageable.

Taking a hard look at company data sources and what is relevant to customer service and call center agents is especially important for businesses to move forward. Quick and efficient support is key in retaining business and maintaining happy, paying customers. With these tools and innovative knowledge management, many dollars and stressful phone calls can be saved.

Trey Norman is the COO at Mindbreeze.

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