Now more than ever, delivering exceptional customer service is vital to a business’ survival as consumers look to cut back on spending in light of the ongoing cost-of-living crisis and wider economic uncertainty.
Often, customer service professionals are the unsung heroes in building and maintaining a sustainable business, so ensuring that they are sufficiently equipped to meet consumers growing demands has moved beyond a nice to have. It’s become a matter of business survival.
We spoke to Matt Bunn, co-founder of Scaling Partner, and Chibeza Agley, co-founder and CEO of OBRIZUM, about the value of AI-powered adaptive learning, and the role it will play in driving customer service beyond basic survival and towards more sustainable business growth.
- What are the challenges of retaining talented staff?
Matt: “Contact centres are facing the pressing issue of rising operational costs adding to the fact that customer service roles continue to experience high attrition rates.
“As agents feel the frustration of lengthy, repetitive onboarding processes, organisations are finding it increasingly difficult to find and retain top customer service talent to manage customer relations and protect brand loyalty.”
Chibeza: “Additionally, for the agents that remain, once they are deemed skilled enough to deal with customers, the work that greets them is often unfulfilling and stressful, requiring them to work long hours to meet incoming demands.
“Given that, with time, agents become more familiar with the company and develop a deeper level of understanding around the types of incoming queries and how best to deal with them, organisations would greatly benefit from retaining these experienced individuals.
“The key is to become more productive and efficient.”
Matt: “For example, contact centres are returning to onshoring as the need to focus on quality over cost effectiveness becomes ever more apparent.”
“It’s during times of intense stress and pressure that the true value of these individuals is realised. It’s unsurprising that we’ve seen contact centres double down on their commitments to agent wellbeing in the face of the economic challenges.”
- How does adaptive learning help?
Chibeza: “When it comes to training customer service professionals, one of the key metrics that managers should focus on are speed-to-competency and total call handling time.”
“Analysis shows that around 17% of customer service agents leave the company without answering a single customer call due to how long it takes for them to be deemed ‘competent’ enough for client-facing environments. The problem is, organisations still use long-winded, laborious, linear training programmes where each person, regardless of prior experience, is taken down the same learning pathway.
“But in reality, we know people learn in different ways and so linear learning fails to cater for unique needs.”
Matt: “This is where adaptive learning comes in. It provides a far more effective way of upskilling an individual to the point that they can demonstrate expertise in a specific subject area. By taking each learner through a tailored learning journey, these non-linear models fast track those with more baseline capabilities while providing the necessary levels of granular detail for those that need it.”
Chibeza: “Non-linear adaptive learning has already increased the confidence and capability of agents and this has been translated into significant improvements in call quality . Not only are calls dealt with more quickly, but customers are also left far more satisfied with the outcome. Additionally, an effective learning model will make onboarding agents far more cost effective.”
Matt: “People still want to speak to people, especially when it comes to more emotive situations. Whilst artificial intelligence and its conversational capabilities are incredibly powerful tools, there are certain aspects of the customer service role that stand well outside its capabilities. It’s therefore vital that agents are trained to the highest level to manage the situations that cannot be automated by technology.”
- What is the value of data-driven decision making?
Chibeza: “The best business practice is to make decisions that are based on strategically collected, relevant data.”
“OBRIZUM’S adaptive learning has a unique feature called the ‘confidence matrix.’ It requires learners to rate how confident they are in their responses, avoiding the ‘quick click’ approach that finishes assessments at a faster rate. In turn, the confidence statistics provide the management team with a true reflection of an individual’s knowledge in a particular area of expertise.”
“It’s also designed to give the individual a greater sense of self-awareness which is directly linked to being a better-quality learner. By encouraging a more thoughtful approach to learning programmes, an accurate picture is painted of a workforce’s skill levels. For customer service professionals, organisations can assign agents to their priority customers based on their skill levels, further supporting brand loyalty and general retention.”
Matt: “In a nutshell, an effective learning programme reduces business risk and improves overall quality and output.”
“Through the partnership with OBRIZUM, Scaling Partner is proud to have presented the business case of non-linear adaptive learning to several large corporate and public sector organisations. As a result, these companies have reaped the benefit from accelerated time-to-competency and reduced the call handling times of their customer service teams.”
“In a time where every penny counts, non-linear adaptive learning holds the key to transforming how customer service is learnt, harnessed, and delivered.”
Chibeza: “We were able to approach larger corporations with our solution with the help of the Scaling Partner team who had the experience and knowledge of working with large customer service teams.
“With so many startups creating solutions to help solve problems in the customer service sector it’s hard for enterprises to know which new AI technology to go with. Through mutual partnerships and a strong focus on data-driven decision making, we’ve been able to ensure our solution is the best market fit so customer service managers know they are getting the best solution out there.”
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