Knowledge Management
Attensity’s Knowledge Management technology provides a core system
leveraged across the Attensity application suite for capturing,
storing, maintaining and sharing knowledge. This system was designed to
enable users to easily and quickly create and share knowledge further optimizing customer interactions whether customers are self-serving or engaging with via a service agent. Attensity Knowledge Management feeds
both Attensity’s Automated Response Management and E-Service
applications with relevant information providing the right information
to help solve customer service inquiries that come in via email, SMS,
fax, phone and text message.
Dynamic Decisions Trees that Drive the Right Information to the Right Person at the Right Time
A
dynamic decision tree capability forms the backbone to the Attensity
Knowledge Management system. Decision trees are a hierarchical
structure of decisions which lead to a solution for a particular
problem. Originating with an initial question, the tree branches off to
indicate possible answers and follow-up questions and, ultimately,
delivers the most plausible solutions. The service agent runs through the decision tree guiding the
service interaction in a step-by-step diagnosis process by responding
to predefined questions in order to ultimately find the solution that
meets the customer’s need. Using this decision tree capability
Attensity E-Service users are able to leverage the knowledge base providing relevant content to the contact center agents and directly to customers online,
thereby delivering resolutions and ensuring customer satisfaction.
Unlike
static decision trees, dynamic decision trees, take problem context and
problem description into account, where problem facts are intelligently referenced in order to answer questions automatically. The service
employee no longer needs to ask or answer unnecessary questions,
thereby reducing query processing time and increasing professionalism
and service quality.
Attensity’s Knowledge Management system
offers a modularization of decision trees into reusable objects and the
parameterization of modules drastically reduces the number of decision
trees that have to be created and maintained. User role concept allows
for simultaneous use of the same decision trees by experienced and
inexperienced call center agents, as well as self-serving customers.