32. “If you can’t explain it simply, you
don’t understand it well
enough”
Editor's Notes
Albert helps agents get to the knowledge they seek with minimum effort, they can search using either their own natural language or key words and phrases. The search predictions anticipate what they are looking for and show suggestions just like Google does – but the results are based on cognitive and contextual intelligence meaning we haven’t had to spend any time setting up any manual links or tags.
All knowledgebase articles are designed to make it as easy as possible for agents to find what they are looking for.
For example, the agent always knows to look in the Guides or timescales boxes to find the relevant information
Just like the search, Albert understands and anticipates what the agent may need next – always presenting Smart Links to contextually related knowledge articles.
This smart link technology not only helps the customer and agent experience but saves as huge amounts of management time because there’s no need to set these up, there’s no tagging or manual linking – as soon as new knowledge content is created it is indexed and the search results and smart links are automatically generated without admin intervention.
Finally, a key part of agent engagement and maintaining the health and continued improvement of the knowledgebase is encourage and acting upon feedback from our agent users. All the feedback and suggestions enter a managed workflow in the knowledgebase administration console where we can understand, measure and act upon agent feedback and activity to ensure Albert keeps delivering great practical value.
This smart link technology not only helps the customer and agent experience but saves as huge amounts of management time because there’s no need to set these up, there’s no tagging or manual linking – as soon as new knowledge content is created it is indexed and the search results and smart links are automatically generated without admin intervention.
There's also a decision tree which we use extensively. These decision trees guide our agents through complex procedures or diagnoses – if we need more information back from the caller before we can provide an answer, decision trees ensure we ask the right questions and reach an accurate conclusion.