Managing the intersection of KM and exceptional customer experiences
The importance of quality, effective customer experiences (CX) has never been more crucial. With opinions on companies and their products shared to wide audiences instantaneously, the customer experience, at all of its increasing number of touchpoints, must be recognized as a pivotal component to the proprietary makeup of a business.
Key to cultivating positive customer experiences is knowledge. Good knowledge management practices—based on rapid availability, self-service tools, quick response times, 360-degree customer views, and seamless, omnichannel experiences—separate the half-way engaging companies from the ultra-customer-savvy.
Experts in CX joined KMWorld’s webinar, Top KM Practices for Optimizing Customer Experience, to discuss the top KM strategies for inviting top-notch CX, including approaches to customer context, knowledge creation tools, standards, and workflows, AI-powered tech, and more.
John Chmaj, senior director, KM strategy at Verint, explained that the customer engagement gap—or the increasing expectations for how well CX and support should be done across channels—is partly due to a lack of automation. The goal, then, is to automate as many facets of CX, without losing out on quality, and involving as little labor—and its associated costs—as possible.
“We’ve come a long way since the search box and the results lists of the 90s, where that was kind of your knowledge management experience,” said Chmaj. “We’re in the era now—especially with AI and a lot of the automation tools—of what we could call CX automation, where knowledge is embedded in platforms, embedded in different tools, [and with] lots of different applications to get at information.”
Aligning with the era of automation, Verint KM closes the engagement capacity gap by reducing the effort, time, and cost necessary to meet increasing customer interactions and expectations. Verint offers the following capabilities to enhance the customer experience:
- Search automation that allows customers to search and find information using natural language at the speed of conversation
- Self-service knowledge automation that presents relevant knowledge to the customer “in the moment,” without the need for manual search
- Simplified knowledge management accompanied by rapid content authoring and approval via extensive reporting functions, multi-step approval workflows, and versioning
- Create a single piece of content once for many audiences
- API-first approach that embeds knowledge at every customer touchpoint, including websites, chatbots, IoT, and more
- Continuous improvement via intuitive feedback loops that offer integrated insights that improve CX
Knowledge is the oil that runs the engine of the business world, according to Pat Hoeffel, head of partner success at Lucidworks. To maintain that oil, Hoeffel identified five key KM practices that are essential to optimizing CX:
- “Relevant results” are the #1 requirement.
- Put the user in control of their experience.
- Reduce cognitive load.
- Make a human connection.
- Provide a unique and immersive experience.
Hoeffel explained that the concept of relevant results is Lucidworks’ “bread and butter,” as well as exactly “the thing” that users want to buy. The technology that drives relevant results has built atop one another, beginning from keyword searches to semantic vector search, neural hybrid search, and finally, generative results through RAG and AI chatbots. Based on this building block pyramid, generative AI (GenAI) and RAG, delivered through AI chatbots, should include all the nuances and components of its predecessors.
To integrate the latest technology with the aforementioned key KM practices, enterprises must strike the “just right,” Goldilocks-esque balance between “too much” and “too little.”
Businesses should seek to provide users with control, but not overwhelm them with too much automation or manual tasks; search should be intuitive, but not too simplistic; tech should be personalized and human-adjacent, but not too uncanny; experiences should be unique and surprising, but not too dramatic. Finding the equilibrium between all these attributes—and committing to the effort of doing so—will give enterprises a competitive advantage in today’s overcrowded market.
Chantal Schweizer, practice director, strategic data services at Pivotree, emphasized the importance of a frictionless commerce experience, especially as it relates to the product data component of KM. Your ecosystem is only as good as your data, Schweizer pointed out, and organization is key to that success.
What does good product data look like? Schweizer explained it succinctly: complete, clean, consistent, and clear. She further recommended that taxonomy best practices—including attribution taxonomy, schema, normalized fill, and governance—are crucial drivers for cultivating a positive product data ecosystem.
The value of complete product data, as it relates to CX, is extensive. Not only can it increase revenue, decrease time-to-market, and reduce the costs associated with new product onboarding and ongoing maintenance, it can:
- Enhance the recall and precision of search results, increasing the likelihood of customer purchase
- Enable cross-sell and upsell
- Decrease employee search time and improve communication
- Create an efficient data line for syndication, commerce, and publishing endeavors
Like the previous speakers, Schweizer also emphasized the importance of automation, particularly as it relates to data classification and enrichment. With automatic content sourcing, automatic classification, automatic normalization, AI-powered descriptions and SEO, and AI-guided, human-powered question/answering, enterprises can merge the powers of modern tech with effective CX at a necessary level of efficiency.
For the full discussion of top KM practices for CX, you can view an archived version of the webinar here.
Companies and Suppliers Mentioned