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Self-Service Comes of Age - Part II
Cliff Conneighton, Senior VP, Marketing, Art Technology Group, Inc.
 Self-Service Comes of Age - Part I
A Framework for Understanding Self-Service:
In general terms, self-service can be classified into two types: informational self-service and transactional self-service. These two phases of customer support and service may span multiple interactions over time across multiple customer touch-points, but should be treated as a single attempt by the customer to get service until complete satisfaction is achieved. Together, they provide the traditional roles provided by a service agent, and fulfill the customer requirement to gain knowledge required to make a decision, and then act on it.
Informational Self-service
Informational self-service uses Web-based tools that allow customers to quickly and easily get answers to questions or retrieve information that will help them solve a problem. Informational self-service is not limited to the customer's perspective, but also includes the functions and processes required within the business to capture and organize knowledge in a way that will be useful and presentable to their customers.
Transactional Self-service
Transactional self-service makes customer-oriented transactions directly accessible to the customer. It covers any function provided to a customer that will allow him to invoke, or gain visibility of, change within the business. It also covers any function that will require back-office applications or transactions to be invoked in order to retrieve customer-specific information such as order status or account balance. Forrester Research further refines this self-service classification by examining the degree of complexity of a question being asked by a customer, and the specificity of the answer. By classifying the nature of questions and answers, four quadrants can represent different types of interactions that a customer requires.
• Simple question, generic answer - A survey in most call centers about the types of questions asked by customers will typically find that they mostly receive relatively simple questions that require the same generic answer, regardless of who is doing the asking. These types of question/answer pairs may broadly be classified as Frequently Asked Questions (FAQ's), although for some businesses this may be a great oversimplification of the subject matter. In terms of technology, this quadrant represents potentially one of the easiest to automate, and considering the volume of call types that may fall into this quadrant, it can also represent the largest area of cost saving if callers can be diverted to the self-service channel. The majority of these types of interactions require basic informational self-service.
• Simple question, user-specific answer - Simple questions can also require answers that vary by individual or groups of individuals. The litmus test is simply, "…it depends whose asking". Account management, for example, requires access to information that is not held in knowledge bases, but resides in back-office transaction systems that need to be accessed for the correct information. After some analysis, a large percentage of these types of questions will be found to be predictable, and so as long as the intent of the questions can be determined, the appropriate transaction can be presented to the customer. Transactional self-service is highly applicable, but informational self-service is also relevant when introducing the notion of revealing different sub-sets of information to different types of customers based on their role or security profile.
• Complex question, generic answer - Complex questions with generic answers are typically found when the complexity comes from the nature of the product or service that is the subject of the interaction, and where a customer is trying to solve a problem through a series of interactions.
The customer is trying to hone in on a solution to an issue, perhaps through guidance, rather than discovering an immediate and obvious answer to the question. Such interactions may be supported by some pre-defined path or decision tree that captures the knowledge of an experienced customer service agent or technical support analyst. The iterative and guided nature of these types of interactions is heavily swayed toward informational self-service, although once a solution to a problem is found, the final step may require a specific customer-oriented transaction.
• Complex question, user-specific answer - Analysis of the types of inquiries handled in a call center often shows that a relatively small percentage of inquires are complex and user-specific. The nature of these types of interactions may still be reasonably answered by a service agent, but may be hard to automate as part of a Web-based self-service application. The cost of trying to handle these types of inquiries through sophisticated self-service may outweigh the benefit. If customers fail to resolve complex, user-specific issues online, they will likely try a human channel anyway, and contact the call center. Thus, a self-service application that knows it is handling a complex, user-specific inquiry, and cannot provide an answer in the first couple of attempts, may help the customer escalate the inquiry to another interaction channel, especially if the customer is highly valued. For a self-service application, there are other options to help the customer besides allowing the Web-based interaction to end in failure.
The convergence of Web and call center technologies has created a number of assisted service channels that can lead the customer from self-service to assisted service, and from assisted service to full telephony-based service as a last resort. A commonly implemented assisted service channel is real-time customer/agent chat. In this context, the customer is presented with a chat window much the same as any common Instant Messaging application, but at the call agent's end sophisticated queuing and routing of the chat request is being used, and the agent is presented with numerous tools to help manage multiple chat sessions simultaneously. Considering the complexity and nature of the question and answer of a self-service interaction is an important stage of assessing the usefulness of the application.
A business needs to assess the degree to which its most common inquiries can be automated. If the self-service application has a poor ability to get quick answers to questions, customers will resort to channels where they can get answers, and investment in the self-service application is wasted. Thus, a framework for understanding the requirements or business need for self-service applications can be characterized by the following elements, of which a business must make its own unique assessment:
1. The complexity of inquiries, and the degree to which a non-human application can understand their intent.
2. The nature of the answers, and the degree to which they are generic or user-specific.
3. The cost and benefit of exposing corporate knowledge directly to the customers, albeit in an enriched, customer-friendly way that aims to solve their problems and give them additional guidance.
4. The cost and benefit of exposing customer-oriented transactions directly to customers in a way that will allow them to be self-sufficient in performing their own actions.
5. The split between the question and answer types that are handled by the call center today to help understand the cost justification.
6. The degree to which a 24x7 customer service channel would be beneficial to improve customer convenience and loyalty.
7. The degree to which the self-service channel can be used to drive revenue by means of contextual guidance.
In the third and final part of this series about self-service, the article will explain proactive self-service and how this is a critical element of the overall framework. It will outline specific examples as well as the umbrella of Customer Experience Management- the imperative for successful customers self-service.
Self-Service Comes of Age - Part III
| Cliff Conneighton is the senior vice president of marketing at ATG (Art Technology Group, Inc., NASDAQ: ARTG). ATG delivers innovative software to help high-end consumer-facing companies create a richer, more adaptive interactive experience for their customers and partners online and via other channels. He can be reached at cconneighton@atg.com
Art Technology Group, Inc.
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