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5 ways to improve CX with AI-infused knowledge management

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As a concept, AI is easy to grasp, but getting tangible benefits from it has been another story. Early AI tools made headlines upon their market launch in the last decade, but something happened. Companies discovered that applying them to the messy reality of corporate systems was often an exercise in dashed expectations and lost value. Those days are behind us.

AI-infused knowledge management tools can also deliver immediate tangible benefits, and because their work is behind the scenes—serving up the right information to self-serve customers or to contact center agents answering complex customer questions. They go right to work improving the customer experience (CX) across call center, self-service, and back-office channels.

Here are 5 things KM tools can do across an organization.

  1. Create a Knowledge Epicenter

For many companies, the corporate knowledge base is a vast pool of data that is poorly organized, difficult to update and too tangled to benefit CX in any meaningful way. What if there were a way to pull from that pool exactly the right piece of data any time customers and employees need it—a sort of drip irrigation system, constantly watering self-service and assisted-service interactions with information that is actionable, relevant and up-to-the-minute?

AI-infused KM tools can do this, pulling from the knowledge pool exactly the right information customers and agents need. They are built with millions of contextual associations that are part of the brain of an AI-infused KM system, so they can anticipate what customers are trying to do and provide the right answer, often before the customer even asks the questions. They can enable your agents and customers to find up-to-date information using every day, common language.

The new tools are working well for a multinational automaker that wanted consistent, accurate information easily available wherever it is needed—to customers in self-service mode, as part of an advisor-assisted engagement in the contact center, or by staff in retail stores.

The company also looked to improve call advisor training and onboarding, to increase call and email deflection to self-service where preferred by the customer, and to keep dealerships across Europe up to date with increasingly complex products and services.

With countless store interactions involving 10,000 retail staff and more than 1,000 employees, the new system has wide-ranging benefits. AI-infused KM has made it easy for customers and staff to find and share knowledge.

  1. Eliminate Customer Frustration with Self-Service

We’ve all been through the annoying experience of being driven down a certain conversational path by a chatbot on a website, where a question-answer cascade can take forever to pinpoint the exact answer we need. That’s self-service with friction. The new KM tools can help reduce it.

For example, generic KM systems use the same metadata label on all customer questions about returning merchandise. New AI systems trained with custom data sets can distinguish between questions about mail drop-offs and in-store returns, total health coverage or supplemental coverage for Medicare. They offer an essential sentence or paragraph pinpointed to the specific question, not a lengthy document or page of FAQs for customers to plow through.

  1. Create a KM System that Learns on its Own

In addition to pre-packaged contextual associations, machine learning can add another layer of depth to new AI systems. For example, the tools can monitor the searches customers perform on a website and note the keystrokes or additional questions the customer asks before the search ends. They then use what they have learned to refine the responses to future searches.

The tools anticipate the answer or best next action based on previous interactions—whether by a customer on a website or an agent using a CRM or other desktop application.

  1. Create a KM System You Can Easily Update

The tools make it easy for employees to contribute to the knowledge base in a way that is more than simply dumping new content into the informational swamp. With AI, the knowledge base keeps itself organized, including putting new content exactly where it needs to be.

For example, Standard Life, a global investment company with operations across Europe, searched for a way to provide its network of 40,000 Independent Financial Advisers (IFAs) with comprehensive and accurate online answers to questions from its two million pension customers. A new KM system uses a dynamic, self-organizing, self-learning knowledgebase that is populated by Standard Life’s staff.

A simple, automated email workflow lets staff members easily create, submit and approve content to the knowledgebase. Content approvers can publish the content in two clicks, at which point the KM system automatically links it to other relevant documents and prioritizes it with other information in the knowledgebase. Content is instantly searchable using natural language questions, so customers can automatically find the exact answers they need online.

  1. Use KM to Share Knowledge in New Ways

Today’s employees expect the personalized experience of Amazon and the speed of Google. Why shouldn’t they be able to access their HR content the same way?

United Utilities, a rapidly growing UK utilities company, used the new AI-infused KM tools to create a “first call resolution” platform that is available to the company’s 5,000 employees 24/7 on any device, including smartphones. As a result, the company achieved a 50% reduction in employee calls to HR and saw a significant increase in employee engagement and satisfaction.

United Utilities also achieved 3x better HR service with the new system. Not only was there a dramatic improvement in employee self-service, but also improved consistency and responsiveness on the part of the HR team.

In another use case, an international catalogue retailer uses the new tools quite innovatively. The company built a C-level portal where executives can get real-time updates on media coverage and any PR issues facing the company. It’s an easy way for the execs to avoid being blindsided by morning headlines and keep company messaging consistent without the need for meetings or conference calls.

KM can also speed up the deployment of an IVA, which needs conversational models to work effectively. Traditionally, organizations have had to build these models, but the work can be accelerated by using the learnings that already exist within the KM system.

Making information actionable, reusable

The authors of the 2008 book, The Best Service Is No Service, claimed that customer service is only needed when a company does something wrong. It was a catchy title that got a lot of attention back then.

However, customers will always have questions. It’s the challenge for competitive companies today to provide the answers in a way that is frictionless—fast, convenient, satisfying, without any “we’ll get back with you” hitches.

That’s the beauty of AI when it’s applied to KM. It’s a way to make AI not some esoteric concept, but practical and actionable. By making the most relevant information shareable, reusable, and updatable across the organization, AI-infused KM tools can bring an organization closer to the holy grail of frictionless service.

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