Contact centers often deploy AI to cut costs. As such, they monitor its success through the lens of handling times and contact volumes.
That’s unsurprising. After all, much of the contact center AI messaging swirls around its potential to drive efficiencies. But that’s just half the story. AI also offers significant potential to make money.
Consider an automated quality assurance (QA) system. Sure, it can help spot opportunities to reduce repeat contacts, shorten interactions, and add automation. However, it may also spotlight best practices and agent behaviors that help boost customer satisfaction and loyalty.
As such, service leaders should challenge the efficiency-centric narrative surrounding contact center AI and take a broader view when measuring its success.
In doing so, they can either bolster their business case for future investment or spot potentially unintended consequences of the AI implementation, which urgently need addressing.
Ultimately, getting this right comes down to the fundamentals of contact center reporting. It requires a balanced approach to measuring critical customer, employee, and business outcomes.
Set Internal Customer, Employee, and Business Benchmarks
The key to measuring the success of AI is: how will we know success when we see it?
Think of that question through the lens of the customer, employee, and broader business. How will each critical stakeholder view the success of this AI implementation?
From there, contact centers can decipher the most relevant metrics and ensure they take a holistic approach to measuring what matters most.
Consider the implementation of a customer-facing virtual agent.
From a customer perspective, they want efficient, hassle-free service with a first-time resolution. As such, the contact center may wish to monitor metrics such as goal completion rate, missed utterances, escalation rate, return users, and customer sentiment – the same outcomes, in fact, that would be measured for a human agent.
Meanwhile, contact center employees may hope to handle more engaging and fewer repetitive conversations with a less intensive workload and less stress. Therefore, the contact center can consider tracking metrics such as agent sentiment, occupancy, and service level.
Finally, the business wants cost-efficient service that maximizes revenue. As such, consider KPIs such as total interactions, cost to serve, and overall cost of operations.
Nevertheless, Steve Nattress, VP of Product Management at Enghouse Interactive, warns:
“It’s essential to understand the nuances of each metric. Some are counterintuitive, like average handling time (AHT), which could actually go up for live agents handling more complex calls while the AHT for AI-handled calls goes down – but they still tell a story.”
After closely considering these metrics, create a picture of where the contact center is today across each. Then, define goals that reflect a broad interpretation of AI success.
But accept that achieving those goals isn’t the be-all and end-all. If the contact center misses some of these targets, it gains insight that may bolster its AI strategy over the long term.
Use Dashboards to Tell the Full Story
To monitor how AI impacts those critical cross-stakeholder benchmarks, build multiple reports onto a single screen, gain insight at a glance, and seamlessly track progress.
A CCaaS provider should present dashboarding solutions to make this possible. For instance, Enghouse Interactive allows its customers to unify reports from cloud solutions, on-premises systems, and even spreadsheets.
Project leaders may even set alerts for when the business is hitting significant milestones while striving to meet its goals. They can then share progress updates with the broader team to celebrate successes, enable further buy-in, and build confidence in AI.
Yet, when dashboarding these metrics, keep them in their customer, employee, and business subsets. That will ensure that the business maintains a balanced focus when measuring success.
Additionally, these subsets may help leaders tell a story to each stakeholder of how AI is helping them and offer reassurance that their requirements are front of mind.
Gather Continuous Feedback
Sometimes metric results can drive misconceptions. As such, it’s best practice to back up dashboards with continuous feedback from both customers and employees.
For customer-facing AI applications, like a virtual agent, utilizing a voice of the customer (VoC) solution to stream relevant feedback into the dashboard may work well.
“You can also use AI to analyze open-ended responses,” adds Nattress. “This gives you more insights and could point to the next problem you need to address.”
For example, an Enghouse banking customer implemented a program to gather information about its mobile application via a survey that contained open-ended responses.
However, when they used the EnghouseAI VoC Insights solution to analyze the customer responses, not only did the bank receive the information they were seeking about the mobile application, but they also uncovered over $3MN in business that they were at risk of losing – for reasons that had nothing to do with the mobile application they were researching.
The end result? A better mobile application for customers, and the ability for the bank to improve retention by showing that they really listen to their customers’ needs and take action.
Speak to the Experts
Since the first speech recognition and natural language processing models (NLP) entered the contact center over a decade ago, Enghouse Interactive has helped customers ensure that their use of AI drives return on investment (ROI).
In that time, the global contact center provider has learned critical lessons on managing AI implementations, through the testing, measuring, learning, optimizing, and deployment phases.
As Nattress is fond of saying: “We have more PhDs on our AI team than employees,” and this wealth of knowledge has allowed Enghouse to develop AI solutions that are tailored specifically for the contact center and CX space.
That knowledge and depth of experience is especially critical as many service operations cautiously step into the unknown and wish to work with a more consultative, hands-on vendor.
To find out more about Enghouse Interactive’s practical solutions for smarter CX, visit: https://www.enghouseinteractive.com/products/enghouseai/
