Self-Service Strategy
The benefits of self-service are profound. When done correctly, it becomes the path of least resistance and best results for the audience you serve. The goal in designing the self-service mechanisms is to provide access to knowledge with the least amount of effort on the part of those who are seeking knowledge. We have learned that designing such a system is not trivial. To deliver self-service in a way that minimizes the requestor's effort and maximizes their success requires careful thought and planning. If done well it is mutually beneficial for both requestors and responders.
Have a Strategy and a Process of Continuous Improvement
It is important to develop a strategy for self-service. We should be very clear on why we are developing a self-service capability. Some of the items that should be included are:
- Vision statement
- Who is (are) the intended audience(s)?
- Goals: what does success look like?
- Measures
- Assessment and continuous improvement process
The greatest value from self-service comes from viewing it as a customer engagement strategy. It enables us to leverage what we know to support greater user success. While a side benefit of self-service is cost reduction for the organization, it is not a deflection or avoidance strategy.
The Customer Experience
Two key concepts that are fundamental to the Consortium’s work are the Value Erosion and Value Add Models. These models address the dynamics of maximizing customer value realization from our products and services and provide additional context around our efforts to measure channel success.
To summarize: value erosion happens when a customer encounters an issue. We want to minimize value erosion by facilitating customer success in finding a resolution as early in their pursuit of a resolution as possible. Customer service and support has focused on the value erosion model for years, but we have an opportunity to look at how we add value. Can we increase the customer’s capability, reduce their effort, and create a pleasant experience without them experiencing an issue? These can be important components of a successful self-service interaction.
Self-Service Design Criteria
In designing the self-service capability there are five key enablers we have observed about successful self-service models:
- Discoverability - Discoverability is driven by three things (all of which are enabled by KCS): context, structure, and rich environment statements.
- Availability - Most of what we know, that is self-serviceable, needs to be available quickly (also a focus of KCS). While the 90/0 rule (90% of what we know is made available 0 minutes - at or before the time of case closure) is a bit provocative, we continue to learn how time sensitive knowledge is.
- Access - Is it easy to find the self-service access point? Ideally access to self-service is integrated into the user interface and is context sensitive for where we are in the product. If self-service is a dedicated digital experience, is it obvious and easy to find?
- Navigation - Is the navigation in the self-service mechanism intuitive for the users and does it align with the requestor's intent? "No dead ends" ensures there is a smooth way to transition from self-service to assisted support: click to chat or click to submit. Suggested or generated answers provided by AI should always be in the requestor's context, and should not create a barrier between the requestor and assisted interactions. Navigation should provide for browsing and searching.
- Marketing - Self-service requires a marketing plan. The "build it and they will come" model doesn't work for self-service mechanisms. We have to take overt, intentional actions to get requestors to use it. If they have a positive experience (see items 1- 4 above) they will use it...a lot.
A positive experience with self-service means that the requestor will use it again. Not only will they come back, but they will use it a lot; in fact, they will use it more often than they ever requested assistance in the past. As a general rule of thumb, if requestors find helpful information 40-50% of the time, they are likely to use self-service again. This is the industry average for self-service success (see Service XRG for the research). In a mature KCS environment where 90% of what we know is available on self-service immediately, the success rates reported are in the 80-85% range!
Discoverability
It doesn't matter how much content we have available to requestors for self-service - if it is not in their context, they are not likely to be able to find it. This re-enforces the need for capture in the workflow. As we discussed in the Capture practice, it is very difficult to re-create the user's perception of the issue if we are not users, and if we know the answer. Creating articles in the requestor's context requires that we capture their context or experience when they first express it. The second factor for both findability and readability is structure. KCS proposes a simple structure for knowledge articles which helps search engines and AI tools be more effective and improves the users experience. The last key element in discoverability is rich environment statements. The environment statements in the article helps the precision and confidence that we have the correct article for our issue.
Availability
How many articles are visible externally, and how fast? The primary enabler of success with self-service is volume and speed. The goal is to get as much as we know into the self-service channel as fast as we can. For requestors to be successful with self-service, articles have to be making it to a Validated state (depending on the business rules) with audience set to External. In the early phases of the KCS adoption, this is driven by reuse. Articles that are reused internally are moved externally quickly. In the Optimize and Innovate phase, we want to be validating and moving externally as much as we can in the moment. The model of reuse driving validation and external visibility should be a temporary state, because we know from member experience that reuse rates in a digital self-service experience are different from reuse rates in an assisted model. It turns out that requestors will use a good self-service model 10 times more often than they will call us. An issue that one requestor raised but has never been reused internally might be used externally a lot; other requestors would use the information, but would not bother to contact us for an answer. Our goal is to get most of what we know into the self-service model as quickly as we can.
When do we turn on and promote self-service? If our KCS articles are complementary to content we already have in the self-service channel, then an incremental approach might work. If we are building a new self-service knowledge base, when do we have enough content in the knowledge base to ensure a 40-50% success rate? One key indicator of sufficient volume in the knowledge base is when the reuse rate of articles intersects with the create rate for a given domain. Plotting the team's create rate against the reuse rate over time gives us a sense of how often people or machines find something useful in the knowledge base (reuse) versus how often they are creating new articles. When the lines cross it means that they are re-using as often as they are creating, or 50% of the time they are linking to an existing article. It is now time to enable and promote the self-service model.
The point at which the create activity equals the reuse activity indicates there is sufficient content in the knowledge base to enable external requestors to find something useful 50% of the time.
Three caveats: first, the linking quality for the domain needs to be at 90% or above and the linking rate has to be in the 60-80% range. This means the internal users are using the knowledge base (creating, re-using, and improving articles) in the problem-solving process a high percentage of the time. Second, articles must be making it to External visibility/audience. And third, the content has to be in the requestors' context which reinforces the finadability factor.
Access
Designing access to self-service to be obvious and low effort is another key to engaging the audience in self-service. Making the self-service mechanism easy to find for the requestors is not trivial. As mentioned earlier, integrating access to self-service knowledge into the user interface for the product is ideal but typically requires a sizable investment. If you are using a digital self-service experience it is important to make it easy to find by the audience you intend to serve.
Navigation
Research has shown that "no dead ends" is the number one factor for users in deciding if they would use self-service again. "No dead ends" means once the requestor has started the problem-solving process in the self-service channel, they don't have to stop and start over if they don't find something helpful. An example of "no dead ends" in the self-service interface is the click-to-submit (create an incident) or click-to-chat functionality. If the self-service model isn't helpful, there is a graceful transition to the assisted model. Because the self-service activities of the requestor are captured and made available to the responder, the requestor doesn't feel like they are starting over. An in-depth research project at Microsoft found that even when customers were unsuccessful with self-service, they were far more willing to go back to try it again if there were no dead ends.
Another key factor in requestors willingness to use self-service is the availability of multiple ways to find things. People use different methods of finding information based on a number of factors. Options for finding articles include:
- A list of product specific, frequently asked questions or "top ten" articles
- An index or table of contents
- Basic or keyword search
- Advanced search
- AI-powered tools such as generative answers
The other design criteria is understanding the audience's intent in using self-service. What are the top three to five reasons people use the self-service mechanism?
Marketing
The "build it and they will come" model doesn't work for self-service. Once we have taken care of the first four success criteria: volume and speed, findability, and access/navigation, we have to think about how to get requestors to use self-service. Trying to change our requestors' behavior is not trivial. Engaging a marketing specialist is recommended. Get advice from those who understand messaging and communications and build a marketing plan.
In addition to a marketing plan, below are some tactics that have been successfully used to encourage their customers to use self-service. We offer these as observations, not recommendations; these tactics must be evaluated based on the business and customer engagement model.
- Recorded message promoting self-service (when requestors call for support)
- Extended hold times - make self-service the path of least resistance and best results
- Turn off the phones - make self-service the only path. Requestors can only open an incident via the digital experience (we must have high confidence that the requestors' self-service experience will be positive)
- Co-browsing - as a responder solves issues, the requestor can see the responder's desktop and watch them search (teaching them to use the self-service tools)
When sending a requestor a resolution, send them the link to the article in the online knowledge base (promotes exposure) - Provide citations with generated answers. Visible references to information available in the knowledge base lead the requestor to further exploration.
Requestor use of and success with self-service becomes two critical measures to assess the success and health of KCS in the Optimize and Innovate phase. If the articles are not making it to the self-service model or if customers are not using self-service, the KCS implementation will stall.
For some examples of good support digital experiences see the Association of Support Professionals (ASP) list of Ten Best Web Support Sites. The ASP conducts an annual assessment of support sites and the criteria they use is available on their web site. It is a great collection of attributes to use in designing your self-service support mechanism.
Integrating Feedback
The most powerful and valuable feedback about KCS articles comes from the audience using them. Every time a user acknowledges getting value from an answer, that feedback should be visible to all who contributed to the KCS article: the creator, as well as people who reused and modified the article. If an end-user flags a KCS article as incomplete or confusing, that KCS article must be queued for rework.
In order to promote trust and to increase the credibility of the KCS articles, some organizations are making feedback visible to all audiences. A ranking system can be put in place similar to what Amazon.com does with product reviews, or Trip Advisor and Yelp provide for user reviews of hotels and restaurants. This information can feed into the triangulation model for assessing the self-service experience.
An underlying premise of KCS is "the best people to create and maintain the knowledge base are the people who use it every day." As organizations begin to Build Proficiency in KCS and make the majority of what they know available to users through a self-service model, that premise still holds.
This raises the question of how to engage users as part of the process. In fact, as organizations mature to the point where a large portion of their articles are external in a just-in-time manner (lots of KCS Publishers across the organization publishing in the moment), good user feedback mechanisms become critical. Users become part of the quality management process for KCS articles. Here are some of the ways member companies have implemented this when allowing users to comment on articles:
- Some make comments private and ask the user if they want to be contacted about the comment. If the user checks the "contact me" box, the system opens an incident for that customer and it goes into the normal incident handling process. This approach is probably feasible only for high complexity/low volume environments.
- Some make the comment public with a wiki-like section on each article that allows users to contribute their experience and opinions and see the comments of others
- Some allow trusted users (often identified through the community forums) to create and modify articles in the knowledge base. The source of the article or modification is indicated in the article.
- Some have segmented the knowledge base and have a governance model in place that allows all users to contribute to open-source type content.
If an AI-powered tool is generating answers out of knowledge, feedback provided to the AI tool should flow back into the knowledge used to generate the answer.
