The Most Underutilized Self-Service Metric
IndustryView | 2014
Self-service has very quickly become a major customer support channel—yet companies implementing self-service have difficulty tracking it with traditional customer service metrics. Level Zero Solvable (LZS) is a unique metric designed specifically to measure the effectiveness, readiness and usability of self-service channels. Data from our recent survey shows how LZS is being used effectively to measure these three variables and, in the process, improve the performance of entire customer service departments.
In a recent Software Advice survey on Top Self-Service Channel Implementations, we found that KBs and FAQ pages were the most commonly adopted online customer self-service channels. Three-quarters of respondents noted that their business attained significant improvements in customer service outcomes after implementing these and other self-service channels. Both quantitative and qualitative improvements were reported, including a reduction in the number of calls requiring Tier One support and increased first-call resolution rates.
However, data from this survey also showed that page views—the metric most commonly used to monitor the success of KBs and FAQs—is a generally ineffective measure of how well, or how often, these channels solve customers’ problems. So while page views may be widely used, it seems this is not a particularly useful metric for representing the real-world success of a given KB or FAQ.
In this report we examine a lesser-known self-service metric: Level Zero Solvable. LZS is designed to measure the success of KBs and FAQs from the customer’s point of view. It’s used by a small portion of the service departments we surveyed, but those that are using it reported markedly better results with their self-service programs.
KBs and FAQs are developed and refined internally before companies release them to the public. The versions that are posted online for the public to use are usually tested by customer service agents while assisting customers over the phone. That’s where LZS comes in.
LZS is a percentage measure of requests, resolved by customer service agents, which could have been resolved by the customer—if the customer was using the same KBs and FAQs as the agent. It can be thought of as a general measure of how thorough and user-friendly the internal KBs and FAQs are. Though there are several ways LZS can be used to improve self-service channels, it is often used to indicate when an internal KB or FAQ is ready to be released to the public.
LZS measures success from the customer’s point of view.
HDI is the world’s largest membership association and certification group for the customer support and service industry. Rick Joslin, their executive director of certification and training, explains how customer service agents start collecting data to determine LZS in three steps:
The LZS score of that KB or FAQ is then expressed as a percentage: the number of LZS calls divided by the total number of calls. For example, if one out of 10 calls is determined to be LZS for a particular KB or FAQ, then that resource’s LZS score is 10 percent.
The first step is the most important. It’s what makes LZS different from most other customer service metrics. By using the customer’s own specific wording and description of the problem to search the KBs and FAQs, it provides a truly customer-centric measure of success.
LZS is used to determine when a self-service resource should go live.
Service departments track LZS as an internal knowledge resource develops and grows. All things being equal, as the knowledge resource becomes more thorough, the LZS score should continue to climb. Once it reaches a certain number—which varies widely between companies—it’s turned into a self-service resource and put online for customers to use themselves.
This focus on determining when to release to the public is critical to the success of these self-service resources. A resource must be developed well enough that customers are able to use it successfully using their own words and descriptions of problems.
Roy Atkinson, senior analyst for HDI, explains, “If people can’t find their issue using their search terms, then they’re going to turn away from self-service.” And when they turn away, they reach for the phone.
LZS can indicate when self-service resources need improvement.
LZS can also be used to gauge the usability of KBs and FAQs already online. If, for example, a company has extensive online self-service resources, yet customer service agents continue to spend time on issues that those online resources were supposed to resolve, that indicates a problem. It could mean:
In either of these cases, an LZS assessment would show that changes are needed. Most software platforms used for customer service are able to track custom variables such as LZS and could help manage this assessment.
To learn more about how LZS is used in real-world customer service departments, we asked our survey respondents to choose their primary use of LZS. We found that most were using it for the reasons mentioned above: to refine the wording of KBs and FAQs (chosen by 43 percent) and to determine when internal resources are ready to go online (31 percent).
Another use of LZS not mentioned above was cited by 16 percent of respondents: LZS can identify topics that self-service channels are not addressing. By keeping track of customer questions that are not LZS and noting how frequently those questions arise, departments can learn which topics and issues need to be added to their self-service channels.
The focus of our survey was on self-service, the metrics used to track various channels and the improvements customer service departments gained after implementing self-service (as measured by industry-standard quality and quantity metrics). Separately, we asked about the use of LZS.
All respondents indicated that implementing self-service had improved their department’s performance metrics. But most interestingly, those whose departments were also using LZS reported even greater improvements—across every metric—than those who reported not using LZS.
The blue bars show the impressive gains our respondents attributed to the implementation of self-service channels alone. And the orange bars show that the use of LZS was correlated with even greater gains: When LZS was used, the performance gains of implementing self-service increased for every metric listed. The largest increases were for first-call resolution, a 10.8 percent increase, and new agent training hours, a 10.7 percent increase.
There’s a very logical connection here. Self-service improves service department metrics—as it’s intended to do. And LZS is intended to improve the performance of the most popular self-service channels: KBs and FAQs. Thus, it follows that LZS would boost the gains already realized by implementing self-service for these channels. In other words—self-service works, and LZS seems to make it work better.
Only 25 percent of our survey respondents reported using LZS to track or gauge their self-service channels. The travel and hospitality, retail and financial services industries reported using it at the highest rate.
It’s not really surprising that these particular verticals, which often rank highest in customer satisfaction surveys, would be using a metric like LZS and adopting a more customer-centric approach to measuring self-service channel success. At the same time, it’s unsurprising that a lower-ranked industry, such as telecom, wouldn’t.
We should note that the survey was not designed to directly link use of LZS with a self-service initiative’s ability to raise departmental performance metrics. It’s possible that other factors are at play. However, the strength of the correlation between use of LZS and better self-service results makes this finding noteworthy, and it seems very likely that LZS is having the intended effect.
LZS is noteworthy for another reason, as well. The world of customer service is filled with lofty talk of being customer-centric and providing service with the customer’s needs and wants in mind. Yet in practice, these goals are often just buzzwords and catchphrases, taking a backseat to the realities of daily call center operations and the bottom-line metrics used to track them.
Customer service expert Shep Hyken explains what being “customer-centric” means in practice: “It means that the company will take a look at every interaction the customer has [with the company], and at every decision that is being made, and they’ll break it down to even the smallest point and they’ll ask, ‘Is this good for the customer, or is it not?’”
When it comes to the most widely used self-service channels, KBs and FAQs, LZS provides the most accurate answer to this question.
What really sets LZS apart is the first step used to calculate it. Using the language of actual customers as the basis for evaluating and refining a self-service resource that will be used by customers can make it more useful to those who need it most. LZS can help ensure that a self-service channel does what it’s intended to do: help customers solve issues themselves. This, in turn, leads to better service department performance and a better return on self-service channel investment.
To find the data in this report, we conducted an online survey and gathered 171 responses from general managers, directors, managers and supervisors employed in customer service departments in a representative spectrum of industry verticals. All respondents had direct experience implementing or managing self-service channels, and direct knowledge of the success metrics and key performance indicators used to track them. All survey questionnaires undergo an internal peer review process to ensure clarity in wording.
Sources attributed and products referenced in this article may or may not represent partner vendors of Software Advice, but vendor status is never used as a basis for selection. Interview sources are chosen for their expertise on the subject matter, and software choices are selected based on popularity and relevance. Sample sizes for the “Use of LZS With Self-Service, by Industry” chart were relatively small; thus, this data may not be representative of those industries as a whole.
Expert commentary solely represents the views of the individual. Chart values are rounded to the nearest whole number.
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