A primary factor influencing whether customers have positive or negative experiences is still based on interactions between human agents and customers. Even with the use of artificial intelligence (AI)-driven predictions, deflection tools, and omnichannel support, the interactions with human agents are often those that customers will remember the most, and to which they will assign the most weight when assessing their experiences.
The overall CX with a brand is rapidly becoming a key competitive differentiator, so proper agent training and support is required to ensure that live agents are adhering to company standards for CX, as well as putting the needs of customers first.
However, organizations cannot afford to shuffle new hires into all-day training sessions, where workers are bombarded with information that they are not able to connect to the experiences they will be having with customers. That’s why taking a fresh approach to training agents can yield significant benefits, in terms of agent performance, retention, and overall customer satisfaction. The following tactics may be useful in training new agents, as well as keeping existing agents up to date on the latest information they need to serve customers efficiently and effectively.
Consider Using Shorter, More Frequent Microlearning Modules
A microlearning module is an educational strategy that offers small bits of information that is focused on a specific, actionable objective or outcome. This targeted learning tool is capped at about five minutes, and can be incorporated as part of blended learning approach, or within formal training when quick references to specific tasks or objectives are desired. Studies have shown that shorter training modules improve focus and support long-term retention by up to 80%, because this bite-sized content matches the duration of the learner’s working memory capacity and attention span.
Many content types can be used, including short videos, animations, infographics, and quizzes or games. The goal is to focus the content on a specific objective or outcome, as opposed to trying to cover a broad range of facts.
Incorporate ‘Gamification’ into Training Modules
Gamification is the process of adding game-like elements, such as points, badges, and other game features, to otherwise traditional training courses and modules, providing learners with new incentives to retain and synthesize information. Corporate training gamification works in a similar fashion to fitness apps, which dole out rewards, badges or points or reaching specific goals. Learners are rewarded for their achievements, such as demonstrating knowledge via quizzes or solving specific problems. In addition, many gamification elements include a competitive touch, which allows employees to compete against each other and create a chance to bond with each other.
Incorporating competition also can help accelerate learning and retention, compared with using traditional training classes, because agents are incentivized to truly learn and understand information to prepare for quizzes or competitions. Further incentives can be provided, such as gift cards or paid time off, for the winners of these competitions.
Leverage AI-Driven Training Practice Scenarios
Taking a one-size-fits-all approach to CX is foolhardy and inefficient at best, and disastrous at worst, given that a single misstep could result in a losing a customer forever. Taking a similar approach to training agents can also result in lots of wasted time and effort, and, in some cases, can result in driving away potentially great employees.
Today’s organizations have massive amounts of data available to them, which can be analyzed and used to optimize and personalize training programs. Content should be personalized to suit the learner’s needs, recommending suitable content based on past interactions, predicting needs based on their role, and auto-generating content using various content creation algorithms, which can consider the strengths and weaknesses of the learner.
AI can also be used to provide content in the format that best resonates with the preferred learning style of each person. A person’s learning style may be influenced by age, ethnicity, cultural background, level of experience, and other factors. An AI-driven training program can be adaptive, where some modules are delivered via video tutorials to some employees, and in other cases, the content is presented to employees in a text-based format or via a game-based approach.
Granular, Personalized Feedback
Tools such as natural language processing (NLP), which rely heavily on AI and machine learning (ML), can provide individualized feedback on agent/customer interactions, such as pace of voice, number of hesitation words used, whether certain keywords were mentioned, and so on. By using analytics and data, feedback can be provided without introducing the biases of the instructor, and performance data can be compared with others and measured to track performance improvement over time.
These AI-driven analytical insights can also be used to address soft skills, such as measuring emotion, tone of voice, and other elements that impact the customer experience. By tracking customer sentiment during calls or interactions, correlations can be mapped between agent behaviors or words and the overall interaction outcomes. This data can be used in training to demonstrate the impact of seemingly small details that have an outsized impact on CX.
Author Information
Keith Kirkpatrick is Research Director, Enterprise Software & Digital Workflows for The Futurum Group. Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
