Self-service for customer support presents both an opportunity and a challenge for companies today. As an opportunity, self-service provides the means of minimizing the number of routine queries that chew up agent resources while also driving up customer satisfaction with quick-and-easy problem resolution, among other gains. But this presumes that self-service is done well—and therein lies the challenge.
As Metrigy has found in its AI for Business Success: 2024-25 global research study of nearly 700 companies, 49.2% of customer interactions start in a self-service channel today. Of those, 46.3% then require live agent assistance via voice and 38.6% require the same via text. While reasons for not being able to contain an interaction to self-service will vary from instance to instance, a less-than-stellar knowledge management environment may well be a common culprit.
A strong knowledge management discipline, including keeping the knowledge management platform (KMS) used for self-service up to snuff, is crucial for customer experience (CX) today—and all the more so with the use of artificial intelligence (AI), including generative AI. For companies supporting self-service customer interactions, a knowledge management platform provides the tools needed for creating, editing, storing, organizing, and sharing information—FAQs, images, videos, diagrams, and forms—served up in this channel. Customer-facing bots tap into the knowledge store as well, grabbing the information customers need to complete their engagement journey within self-service rather than escalating to live agent.
Nonetheless, only half of the 1,566 companies Metrigy studied for its global Customer Experience MetriCast 2024 buyer-side market forecast study are currently using a self-service knowledge management platform. And there’s no guarantee that the knowledge management platforms in use are proving of real value. Of the companies in the AI for Business Success study, most say that they need to upgrade their knowledge management platform but haven’t yet done so (22.2%) or that they’re still working on an upgrade (32.3%). Even the 30.2% of companies that say they’ve already upgraded their platforms may not be truly well-situated, given the rapidly evolving state of AI technology for CX today.
As companies seek out new knowledge management platforms or work on upgrading their existing platforms, they must do so with the goal of meeting success metrics such as knowledge management’s effect on resolving issues in self-service, percent of self-service cases resolved, and customer satisfaction (CSAT) improvements. These are the three knowledge management-related metrics that Metrigy studied as part of its CX MetriCast research, in which we analyzed the differences between successful and non-successful companies as determined based on measured improvements in select CX metrics.
Looking at the successful customers of the 15 self-service knowledge management vendors we assessed as part of our CX MetriStar Award program, Metrigy found:
- 64.7% measure the link between using knowledge management content and self-service resolution
- They’re able to address at least 44.3% of issues completely via self-service channel, rather than requiring escalation to live agent
- Customer satisfaction score, based on a 1 (worse) to 7 (best) rating, is at or greater than 5.3.
Companies also should bear in mind how customers feel about their knowledge management vendors in use. Do they have positive or negative sentiments on critical factors such as reliability and ease of content management? Metrigy can provide a guideline around customer sentiment, too, using scoring gathered in the CX MetriCast study (based on a 1-to-10 rating scale, where 1 = Extremely Poor and 10 = Outstanding). For self-service knowledge management platforms, overall average customer sentiment score is 8.09, with individual provider scores ranging from 7.51 to 8.71.
To remain competitive in CX, and on top of self-service expectations, companies must address any knowledge management shortcomings they might have.
