Knowledge work tools can reduce costs by helping organisations be more efficient, but that’s not the whole story. They can substantially improve service standards by delivering an improved customer experience that is high-quality, fast and consistent.


Customers already expect self-service, anywhere and anytime with the option for assisted service if necessary.

But it’s not just organisations that want high-quality automated services, it’s customers. The move towards automated self-service is accelerating so quickly that Gartner predict that by 2020, customers will manage 85% of their relationship with the enterprise without interacting with a human.

Modern products and services are complex, so contact centre agents need to have a wealth of experience and knowledge to be able to handle the breadth and depth of today′s customer issues. Contact centre managers agree that the right knowledge delivered to the customer at the right time is critical to a successful interaction. Done well, this can increase customer loyalty, reduce call handling time, and make the operation more efficient.

Traditionally, contact centres have utilised knowledge management systems to achieve this. These are often simple knowledge bases comprising databases of question and answer pairs (FAQs) together with scripts to guide contact centre agents through structured processes. These scripts tend to be based on decision trees using if this, then that logic.


These FAQ and decision tree technologies are severely limited and often fall short of customer expectations. Let’s explore why:

  • They are linear and are not goal oriented
  • They are single-purpose, only capable of answering the question for which they were designed
  • They retain no knowledge of previous interactions with the customer making them an inefficient way of solving a problem
  • They are expensive to maintain because they are subject to regression when things change
  • They deliver a frustrating customer experience


In a recent Forrester report, only 44% of firms surveyed even had an agent-facing knowledge management system at all. In organisations like these, agents fielding complex questions cannot easily access the content they need to reliably answer customer questions, putting the quality of service at risk. Consumers cited their greatest customer service complaints as:

  • different customer service agents giving different answers (41%)
  • customer service agents not knowing the answer (34%)


Technologies like Rainbird can be used to create much more powerful troubleshooting tools with all of the benefits and none of the pitfalls of decision trees. When the human brain solves problems, we join-the-dots in an intelligent way, using the data we have and the prior information we believe to be true (with varying levels of certainty). Rainbird works the same way and is capable of navigating a knowledge structure modelled by the expert themselves. It will draw it’s own inferences, asking the most efficient questions possible to solve a problem, even answering questions not originally conceived by the author.

Rainbird extends the deep and broad expertise of experienced staff to the entire team and facilitates the creation of more flexible and powerful decision support tools for contact agents, as well as the rapid publishing of self-service tools for customers.