Knowledge Management - Knowledge Driven Customer Relationships

Knowledge is power but only when it is deeply integrated into the customer experience, the agent experience, and the enabling technology. Service and support organizations can benefit tremendously from knowledge. When implemented effectively, knowledge management processes and technology can deliver significant benefits:

Support operations are more efficient. Rather than handling customer requests based only on their own experience, all customer-facing staff have access to the collective experience of the whole team. Problems are solved once; agents don’t repeat work that others have done, or bother escalation teams with already known issues.

Customers help themselves. A shared knowledgebase enables call deflection. Effective self-service will remove case load that is low value to the enterprise or an irritant to the customer. This saves money and makes customers happier.

Also, customers can use self-service to receive help on topics about which they might never have called an agent. That is, self-service that is powered by a strong knowledge management initiative will satisfy customer demand for service and support that would otherwise go unmet. This is a very cost-effective way to create value for customers and nurture customer loyalty.

The organization continually learns from its customers. Tracking the ways customers and agents use knowledge provides an ongoing, measurable listening post for the Voice of the Customer. With this information, products can be improved, the customer experience can be enhanced, and service and support can be made more effective.

Every customer interaction is an opportunity to capture, improve, or reuse knowledge. With knowledge at the center of the CRM implementation, every time a support staffer helps a customer, the knowledgebase and the organization as a whole becomes that much smarter. If knowledge exists in the knowledgebase, its use is tracked to drive product improvements and customer outreach programs. If the knowledge is not completely current, certified staff can update it on the fly. If the knowledge does not exist, it can be captured in a simple, structured, reusable form.

Knowledge management deeply embedded inside the case management process helps staff continually create, reuse, and validate their knowledge. With continued improvement, the knowledgebase becomes even more valuable.

Unfortunately, it is almost impossible to receive these benefits unless knowledge is at the very heart of everything the organization does, starting with CRM.

Knowledge management must be the core of any successful CRM deployment, not an add-on module. When knowledge is deeply integrated with CRM, not tacked on as a side dish or an add-on module, enterprises can truly begin to nurture loyal customer relationships.

Everything customers say and do can improve their self-service experience. CRM systems typically advertise themselves as the "customer information repository of record", But customer information sitting passively in a repository serves no purpose. Self-service that is fully integrated with case tracking takes advantage of everything customers have shared to personalize the interaction and efficiently deliver what they need. Self-service can even use configuration and diagnostic information from the customer’s system to deliver precision-targeted information.

Streamlining the agent experience means providing an integrated resolution workbench with a single screen for any tools the user needs. In knowledge driven CRM, both case management and incident management are all part of a single process.

The resolution workbench should proactively deliver knowledge to agents or analysts based on information they have received from the customer to date. Of course, this is just a starting point. Agents must be able to drill in and refine searches on an ongoing basis.

Some of the information that agents, analysts, or engineers want to record is specific to that customer and case, for example, "the customer promised to send me a log file after the next error message appears". But some information, such as symptoms, the root cause, or a problem resolution, is relevant to anyone working on the same customer issue. The support staffer must be able to seamlessly capture both kinds of information on the fly, without retyping, copying, or pasting. As one team member learns something new, all can immediately share in the benefits.

Knowledge-Centered Support (KCS) is the industry standard set of best practices developed by the members of the Consortium for Service Innovation. Its central tenet is that "knowledge is not something we do in addition to solving problems. Knowledge becomes the way we solve problems". In addition to all its other benefits, an integrated resolution workbench is a tremendous accelerator for adopting KCS.

If self-service ends up not solving one particular issue, customers should have an absolutely seamless experience where the agent (via chat, phone, or any channel) can pick up right where self-service left off.

It is hard to read too much into the raw knowledge statistics: just because a knowledgebase article was viewed frequently in self-service, we can’t be sure that it resolved the customer’s real issues. Reporting by resolution categories in CRM rarely gives product developers sufficiently detailed information to take action. But combined knowledge and case reporting, for example, which knowledgebase articles closed the most cases, can provide precision guidance into the root causes of customer frustration.

Also, combined analytics enable specialized dashboards that help managers and executives assess individual and team performance. In a knowledge-creating company, it’s not enough to just measure how many cases were closed or how many articles were written; performance assessment requires a broad view of what individuals and teams are doing, including how their knowledge work improves their case work.

Finally, organizations must quantify and continually increase the business value being generated by the service and support organization. For example, how much demand for support is being satisfied automatically through the website, and how much must still be addressed by agents? These questions lie at the intersection of knowledge and case management. True knowledge-driven CRM can provide clear answers.

Faceted Search

Faceted search, also called faceted navigation or faceted browsing, is a technique for accessing information organized according to a faceted classification system, allowing users to explore a collection of information by applying multiple filters. A faceted classification system classifies each information element along multiple explicit dimensions, enabling the classifications to be accessed and ordered in multiple ways rather than in a single, pre-determined, taxonomic order.

Facets correspond to properties of the information elements. They are often derived by analysis of the text of an item using entity extraction techniques or from pre-existing fields in a database such as author, descriptor, language, and format. Thus, existing web-pages, product descriptions or online collections of articles can be augmented with navigational facets.

Faceted search has become the de facto standard for e-commerce and product-related web sites. Other content-heavy sites also use faceted search. It has become very popular and users are getting used to it and even expect it.

Faceted search lets users refine or navigate a collection of information by using a number of discrete attributes – the so-called facets. A facet represents a specific perspective on content that is typically clearly bounded and mutually exclusive. The values within a facet can be a flat list that allows only one choice (e.g. a list of possible shoe sizes) or a hierarchical list that allow you to drill-down through multiple levels (e.g. product types, Computers > Laptops). The combination of all facets and values are often called a faceted taxonomy. These faceted values can be added directly to content as metadata or extracted automatically using text mining software.

For example, a recipe site using faceted search can allow users to decide how they’d like to navigate to a specific recipe, offering multiple entry points and successive refinements.

As users combine facet values, the search engine is really launching a new search based on the selected values, which allows the users to see how many documents are left in the set corresponding to each remaining facet choice. So while users think they are navigating a site, they are really doing the dreaded advanced search.

There are best practices in establishing facets. They are:

do not create too many facets - presenting users with 20 different facets will overwhelm them; users will generally not scroll too far down beyond the initial screen to locate your more obscure facets;

base facets on key use cases and known user access patterns - idenfity key ways users search and navigate your site. Analysing search logs, evaluating competitor sites, and user research and testing are great ways to figure out what key access points users are looking for. Interviewing as few as 10 users will often give you great insight into what the facet structure should be;

order facets and values based on importance - not all facets are equally important. Some access points are more important than others depending on what users are doing and where they are in the site. Present most popular facets on the top. When determining order for navigation, again think about your users and why they are coming to your site.

leverage the tool to show and hide facets and values - while the free or low-cost faceted search tools don’t all offer these configuration options, more sophisticated faceted search solutions allow you to create rules to progressively disclose facets.

Think of a site offering online greeting cards. While the visual theme of the card – teddy bears, a sunset, golf – might eventually be important to a user, it probably isn’t the first place they will start their search. They will likely start with occasion (birthday, Christmas), or recipient (father, friend), and then become interested in themes further down the line. Accordingly, we might hide the “themes” facet until a user has selected an occasion or recipient. You can selectively present facets based on your understanding of your users and their typical search patterns (as mentioned in the previous “do”).

Also take advantage of the search engine’s clutter-reducing features, such as the “more...” link. This allows you to present only the most popular items and hide the rest until the user specifically requests to see them. You can also do this at the facet level, collapsing lesser-used facets to present just the category name and let users who are interested expand that facet.

facet display should be dependent on the area of the site. If you are in the first few layers of your site, you should show fewer facets with more values exposed, whereas if you are deeper into product information you should show more facets, some with values exposed and others hidden.

create your taxonomy with faceted search in mind - a good taxonomy goes a long way in making a successful faceted search interface.

There are some important guidelines to follow in taxonomy design. Facets need to be well defined, mutually exclusive and have clear labels. For example, having one facet called “Training” and another “Events” is confusing: where do you put a seminar? Is it training or an event? If you have to wonder, your users will too. The taxonomy depth (how many levels deep does it go) and breadth (how many facets wide is it) are other important considerations. Faceted search works better with a broad taxonomy that is relatively shallow, as this lets users combine more perspectives rather than get stuck in an eternal drill down, which causes fatigue. The facet configuration and display rules will help you create the optimal progressive presentation of these facets so as to not overwhelm users with the breadth.

If you are torn between two places in the taxonomy for a term, consider putting it in both places. This is called polyhierarchy, and it is a good way to ensure findability from multiple perspectives. Polyhierarchy is best served within a facet rather than across multiple facets. Since facets should be mutually exclusive, you shouldn’t have much need to repeat terms across facets, which can be more confusing than helpful.

The most important thing however, is to be prepared to break any of these rules in the name of usability. Building a faceted taxonomy involves understanding your users’ search behavior.

As the trend towards increased social computing continues, Web 2.0 concepts are entering the realm of faceted search. We are starting to see social tags being used in faceted search and browse interfaces. Buzzillions.com, a product-review site, is using social tag-based facets in its navigation, allowing users to refine results based on tags grouped as "Pros" or "Cons". This site uses a nice blend of free social tagging and control to ensure good user experience; when you type in a tag to add to a product review, type-ahead verifies existing tags and prompts you to select one from the existing list of matches to maximize consistency.

Ultimately, navigation and search is one of the main interactions users have with your site, so getting it right is not just a matter of good design, it impacts the bottom line. Faceted search is a very popular and powerful solution when done well; it allows users to deconstruct a large set of results into bite-size pieces and navigate based on what’s important to them. But faceted search by itself is not necessarily going to make your users lives easier. You need to understand your users’ mental models (how they seek information), test your assumptions about how they will interpret your terms and categories and spend time refining your approach.

Faceted search can just add more complexity and frustrate your users if not considered from the user perspective and carefully thought through with sound usability principles in mind. Faceted search is raising the bar in terms of findability and how well you execute will determine whether your site meets the new standard.