The 5 Relevance Secrets For Contact Centers: How to Make Customer Service KPIs Soar
Despite lip service across all industries to improve customer satisfaction score (CSAT), it has fallen to its lowest level in 15 years. That’s a problem as a majority of consumers say that after three or fewer negative experiences, they will abandon a brand. It’s no wonder, then, that CEOs are making customer satisfaction a priority over customer acquisition. How can they turn this steep decline around?
Coveo is a search relevance provider that uses unified search, analytics and machine learning relevant information to customer service providers. We examined our highest performing contact center clients — those who had seen CSAT scores jump by nearly 30%, had a 50% increase in self-service success and/or a 25% decrease in case resolution time — to see if we could determine best practices. And the answer was: They all were committed to providing relevance.
So What Is Relevance?
Our analysis revealed how companies gave their customers and call center agents exactly the answers and content they needed, right when they needed it. They used artificial intelligence (AI) to deliver these answers faster than customers could blink. And companies delivered it to not just one customer, but up to millions of customers at a time.
In other words, our customers created data-driven user empathy by getting their customers the right personalized information, answer or solution when they need it. Convenience, simplicity, and personalization are givens to drive relevance. Customers reward companies that provide relevance, with their time, their money, their productivity, and their loyalty.
The big question is, how can other companies deliver on this demand? To find answers and learn from the best, Coveo’s Business Value Team dug into Coveo’s own customer data to analyze what set the top-performing companies apart from the rest. Leveraging technology is only part of the equation, driving high adoption of the technology is key to impacting business results.
Here’s what the leaders in relevance are doing and how you can apply these proven practices to create strong, relevant customer experiences.
#1 Build the Best Relevance Solutions by Bringing IT and Customer Service Together
In 52% of the top performers, the customer service department owns and drives the adoption
of customer service technology; 43% work hand-in-hand with IT. None of the leaders relied on
solely IT to implement the technology, whereas 21% of the bottom performers did.
When the customer service department works with the IT team, the customers and agents win. The customer service team defines what they need and why they need it. They have deep knowledge of critical satisfaction KPIs. And call center agents can influence the adoption and use of the technology to support those goals, whether to increase the self-service rate or improve case resolution time. Meanwhile, the IT team brings the tech-know how to figure out how to make it possible. They then make sure the solution works — and works well.
To make relevant experiences, start with those in the organization who have the most knowledge about what impacts the customer. For customer service, the customer service department should own this conversation. They know what’s most relevant — for agents and self-service — and can help tailor the technology to meet those needs.
#2 Use Machine Learning Models to Improve Search Relevance First
Only a rare handful of top performers don’t incorporate machine learning heavily into their technology. Nine out of 10 top performers use two or more machine learning models. In fact, almost 40% of our top performers (38%) use five or more machine learning models, while only 25% of bottom performers do.
This suggests that the leaders are more capable when it comes to embracing machine learning. The easiest and most impactful models to include first are re-ranking and type-ahead models. The former will better rank search results for self-service customers or agents and the latter will anticipate what exactly the user is searching for.
The second tier for machine learning models will help provide recommendations, answer questions directly in the search feed and classify cases.
Each machine learning model helps identify, sort, and present the most relevant customer service results or recommendations to agents and self-service customers. The model develops these recommendations and results based on an organization’s usage data. When configured, a model can create the best experiences for certain regions, content categories, or audience types.
#3 Ensure all Your Relevant Support Content Is Searchable
Call center agents shouldn’t need to switch between 12 programs or windows to find the required information to solve a case. Oftentimes, each program requires a password at the most inconvenient time. This kind of delay, multiplied by 10,000 calls, is massive.
Agents working without AI technology can spend about a third of their time searching for the right information, Coveo found through other analysis. That’s why the more content sources that are indexed and available to agents through a unified search experience — from technical articles to customer information — the better.
Nearly 60% of top performers indexed five or more external or internal content sources, such as their websites, knowledge bases, CRMs, support communities, and video repositories. In comparison, 70% of the lower-performing companies indexed only one or two sources.
Indexing more content sources makes it easier to create relevant experiences. It brings together disparate information so customer service agents can seamlessly access multiple knowledge sources and better serve customers. It also improves case deflection as customers have more knowledge at their fingertips. When you can find the content you want, everyone is happier.
#4 You Don’t Need a Mature KCS Program to Start Creating
A mature knowledge-centered service (KCS) approach will arm agents with the tools and content they need. It will also help fill the gaps between what customers are searching for and finding. We see it as important in creating relevant experiences for customers and agents.
Though fewer low performers had mature KCS programs than high performers (8% vs. 14%), companies at all stages in their KCS journeys can create strong relevance programs. Surprisingly, more of our top performers have new KCS programs (33%) than either average (24%) or mature programs (14%). This suggests organizations with new KCS programs might be investing more time and resources in them than those with older programs.
#5 Evangelize and Enable New Resources or Technology Changes
Awareness is the first order of change management, so when you’re implementing new tools — especially ones that can help agents do their jobs better — they should be announced and promoted to users.
Find those champions of change to become advocates and encourage others to adopt the new resources, processes, or technologies. Open communication directly with agents for feedback and a closed-loop process to review and implement change can lead to higher satisfaction and tool adoption.
Top performers know this: 52% communicate regularly about ad-hoc updates to the platforms they work with. Of the low performers, only 13% provide regular updates, and 8% implement without announcing the change at all.
Exceed expectations with relevance
It can take a lot to meet customers’ expectations. Don’t settle for only meeting them, exceed them! The five steps discussed above will set you on the journey to do so.
Click here to read the full report and learn more about the Coveo Relevance platform.