![]() XpertRule eServiceThe Challenge of Delivering Expert Technical Support Automating Technical Support Knowledge1.0 The Challenge of Delivering Expert Technical SupportThe increasing complexity and variety of IT, Internet, Telecom and technology products and services being offered to customers and the rapid pace of change of these products and services is increasing the demand for expert customer service. This involves the timely and effective diagnosis and resolution of customer queries / problems that is vital to customer satisfaction and retention. Delivering such support requires an increasing number of highly trained customer service agents. In a commercial environment of increased competition and reduced profit margins, the challenge is how to reconcile the seemingly conflicting objectives of reducing customer support costs while maintaining / improving support quality. The challenges can be summarised as follows:
1.1 CRM / Call Tracking Systems Do Not Improve Customer ServiceInvestment in CRM (customer relationship management) software has done little to improve customer loyalty according to the latest research from IT services company Accenture. A survey of 2,000 customers in both the UK and US found that 61 percent identified poor service or product quality as the main reason for moving between companies. Almost one-fifth of respondents cited technology problems as a reason for their dissatisfaction.Although CRM / call tracking systems are intended to improve customer relations, over one-third of customers complained of being forwarded through multiple company representatives before problems were adequately resolved. "Customers expect the first customer service representative they talk with to have the knowledge, tools and capabilities required to address their needs," according to Robert Wollan, managing partner of Accenture's customer contact unit. Customers spend an average of six minutes on hold while waiting for help on the telephone and speak to an average of 2.6 service representatives before their query is resolved. 1.2 Knowledge Management Delivers Limited Benefits to Customer ServiceCRM systems are being supplemented by Knowledge Management Systems in an effort to improve customer service. The majority of the current generation of Knowledge Management solutions for customer service involve the managing of unstructured knowledge. By managing unstructured knowledge we mean managing content such as documents of various formats, web pages, and similar (emails, textual description of solutions to problems) using search engine like technology. The knowledge management technology normally involves the indexing of these documents (content) and allowing the subsequent search for the relevant documents through keywords search, natural language query or browsing simple hierarchical categories. Other extensions to managing unstructured knowledge include:
1.3 Automation of Support Knowledge Improves Customer ServiceSupport Knowledge Automation (also called Service Resolution Management) captures structured support knowledge such as diagnostic trees, trouble-shoot flows and related service resolution procedures. Once captured, the deployment of such automated knowledge almost eliminates the reliance on the skills of agents in interpreting the knowledge. The agent is guided by the system to ask the right sequence of questions in order to achieve problem resolution in the most efficient and direct way. Support Knowledge Automation can therefore enable agents with minimal training to answer complex queries and problems. The resulting benefits are:
2.0 XpertRule eService - Integrating Structured and Unstructured KnowledgeIn practice, customer service knowledge is a hybrid combination of structured, unstructured knowledge and core customer service interaction skills. The solution to a customer problem/query can be found in a document or in a diagnostic / trouble-shoot tree or procedure. A Customer Service knowledge base consists of tens of thousands of such solutions. The technologies required for a hybrid (structured and unstructured) knowledge management system are illustrated below:![]() Note that unstructured search results in finding a document or URL while structured search using diagnostic / classification trees can lead to a document or other structured knowledge solutions such as trouble-shoot flows. In other words structured customer support knowledge can be split into two stages; the first step is to classify / diagnose the nature of the query and the second step is the resolution of the query. XpertRule eService is a software environment for the capture and maintenance of structured knowledge and for the seamless integration of this knowledge with unstructured knowledge (content). XpertRule eService also delivers the most scalable deployment of structured knowledge on the market today. These breakthrough capabilities are achieved as described in the sections below. 2.1 Knowledge Authoring EnvironmentXpertRule allows the capture of customer service / support knowledge using graphical process flows (trees) representing recommendation, advisory, diagnostic, trouble-shooting and problem resolution knowledge. The Enterprise strength knowledge-authoring environment allows authors to collaborate on capturing and maintaining the customer service knowledge working over a network.The development environment maintains thousands of possible questions and flows (trees). Each knowledge author can work on his/her area of expertise whilst sharing questions and trees with other knowledge authors. The graphical and structured knowledge representation speeds the process of capturing the knowledge and subsequently maintaining the knowledge as the products and services evolve. Extensive technical support knowledge can typically be captured in a few weeks. Integration between XpertRule and a Content Management System (CMS) is achieved by means of an intermediary API to allow seamless integration between XpertRule resources and resources managed by the CMS. Customer Service Knowledge centres around the solutions base. Each solution can have an optional set of attributes. A solution points to a document, or to a knowledge flow / tree. The knowledge-scripting environment allows the maintenance of a large number of questions, advisory, diagnostic and classification trees which are used to narrow down the list of required solutions. The trouble-shooting knowledge consists of flows and trouble-shoot steps. Flows can also contain sub-flows representing common trouble-shoot sequences. The knowledge-authoring environment allows the maintenance of thousands of questions, steps, sub-flows and flows. Each knowledge author can work on his/her area of expertise whilst sharing questions, steps and sub-flows with other knowledge authors. The graphical and structured knowledge representation speeds up the process of capturing the knowledge and subsequently maintaining the knowledge as the products and services evolve. The task of finding the relevant solution(s) that can address the customer question or query is normally called a classification or diagnostic task. By asking a sequence of focussed questions, the knowledge flow narrows down the list of suitable solutions. Below is an example of such knowledge which narrows downs the solution to one of five possible trouble-shoot sequences. ![]() The knowledge for one of the five trouble-shoot solutions is shown below: ![]() Solutions can also be assigned attributes (e.g. Windows Operating System and Internet connection method) that can act as selection filters that further narrow down the relevant solutions to a query. The deployment engine logs all the data from agent sessions to a database. The data captured includes answers to questions, the time taken to capture each answer, trouble-shoot fixes tried and whether problem was resolved. All this logged data is processed by the authoring environment to reveal the statistics for each diagnostic and trouble-shoot flow. This is an important catalyst for improving the knowledge by highlighting "problems" with poor record of resolution rates and identifying which fixes are more effective than others at resolving problems. 2.2 Multi-Channel, Integrated and Scalable Knowledge DeploymentXpertRule offers a unique technology for deploying customer service knowledge across all customer contact channels; telephone, web self-help, email and chat. This is achieved through XpertRule's pure HTML deployment that does not require a rules engine on the server or the client. The classification, diagnostic, advisory and trouble-shoot knowledge scripted in XpertRule is transformed into a set of intelligently linked HTML pages which are stored on a web HTTP server. This unique approach has very many advantages:
For email service agents, XpertRule can provide an AutoSuggest feature that prompts the agents for answers to questions that may be contained in the query email. XpertRule then suggests an email reply which can either be a request for more information or a required trouble-shoot flow which XpertRule can attach as either a graphical tree or a textual set of trouble-shoot steps. Email replies can also include a link to web self-help to continue trouble-shooting. For chat service agents, again XpertRule can provide an AutoSuggest capability for the agent to respond to the customer or alternatively the agent can divert the customer to web self-help.
2.3 XpertRule eService - Technology PositioningThe diagram below illustrates the positioning of XpertRule eService in relation to Content Management (CMS), Knowledge Management (KM), Service Resolution Management (SRM) and Customer Interactions Management (CIM) Systems. This can be summarised as follows:
![]() 2.4 Summary of the Unique Features of XpertRule eService
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