Nykki Yeager
Posted by Nykki Yeager
Mar 10 / 2018 | 0 Comments

Use adaptive learning to increase customer service training efficiency

The goal of most customer support teams is customer satisfaction via quality issue resolution. This, of course, requires a qualified and competent team. And while many teams may believe that their employees have all the skills and knowledge they need, research has shown that employees are up to 40% unconsciously incompetent in areas that are critical to their performance. Meaning, employees are lacking important skills and knowledge, and they don’t even know it.

Adaptive learning data


This unconscious incompetence affects every department, perhaps especially customer-facing teams who need to know a lot. One company found that its sales employees didn’t understand or know about 22% of its product features, even though they thought they did.



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This same risk, quite possibly an even bigger one, exists for customer support teams -- because in order to answer the broad spectrum of questions that come their way, support teams need to know the full product inside and out, as well as just about everything about every point of the customer journey.

When customer service employees are subconsciously incompetent, they make mistakes and produce lower-quality work, affecting both the customer experience and the business bottom line. Not only might a mistake cost a lost customer, attempts to fix mistakes require extra time and labor, which increases business costs. Mistakes also keep your team from reaching its goals, driving down morale and undermining your impact and authority in your business.

It’s likely that your team already has a long list of mistakes to fix and ways to improve, especially if you’re doing quality co-listenings or transaction monitoring in your contact center. It’s also likely that you’re relying on employee training as a tool to help you meet those improvement goals.


Traditional customer service training is broken

But traditional training practices are inefficient and ineffective. They tend to take up a lot of time, during which, employees aren’t doing frontline work. And thanks to something called the forgetting curve, all the knowledge gained during training can be easily lost if there aren’t deliberate attempts to retain it. The forgetting curve is a mathematical representation of the loss of knowledge over time. In fact, up to 70% of what’s learned can be forgotten within 24 hours.

Ebbinghaus forgetting curve

Traditional training practices don’t ensure true proficiency. Measuring learning by the number of hours spent studying or the number of courses completed doesn’t prove mastery. However, demonstrating the knowledge and skills in practice does.

To boot, the one-size-fits-all model of traditional training is inherently boring and unengaging, because it doesn’t involve the learner in designing the course, nor take into account the learner’s existing skills or learning speed. Many employees simply speed through training modules to get them over with, because they’re not actively involved in the process.

And if all that weren’t enough the, traditional training is usually prescribed reactively, after the discovery a mistake or deficiency, which means it doesn’t address the problem of unconscious incompetence.


Enter adaptive learning

Adaptive learning combines aspects from various fields of study including computer science, education, psychology, and brain science. In a nutshell, adaptive learning uses technology to produce personalized and interactive experiences by modifying the presentation of material in response to each unique learner. With an adaptive learning solution, content can be adjusted in real-time based on the learner’s strengths and weaknesses, as well as their responses to questions and tasks.


A tailored approach for each learner

Because it adapts to each situation and learner, adaptive learning has been shown to reduce training time by up to 50%.  People learn in their own ways and have different starting points in their knowledge. A new employee, for example, is going to have entirely different needs than a seasoned employee. A tailored approach means that learners are only spending time on the things that they personally need to study.


Repetition based on the forgetting curve

Adaptive learning also tackles the problem of the forgetting curve by ensuring review of the material at intelligent times. Each learner’s forgetting curve can be modeled so they get a refresher on specific material just before they’re about to forget it. Instead of waiting for front line employees to make a mistake, adaptive learning proactively prevents them from forgetting the knowledge in the first place.


 Proficiency through continuous self-assessment

True proficiency is achieved as employees put their skills into practice and develop confidence in their own abilities. If an employee knows something, but isn’t confident about that knowledge, then they need more practice in order to have true mastery. They may be passing courses simply through lucky guesses. Adaptive learning increases confidence and proficiency through continuous self-assessment. Learners rate how well they think they know something before the answer is revealed. This data is used to help personalize the learning experience.


A more engaging learning experience

Plus, since adaptive learning actively involves the learner and teaches responsively, it’s naturally engaging. When employees are invited to participate in steering their own training, while at the same time are being challenged, the experience is more captivating and effective.

In addition, through probing and exploration, adaptive learning technologies can illuminate where employees have knowledge gaps and help remediate those areas. With an approach like this, employees learn what they don’t know, bringing it to light and allowing them to improve. Adaptive learning actively reduces unconscious incompetence.


Adaptive learning in practice

Adaptive learning works best when content is broken into very small pieces, which allows for a higher degree of personalization as content is swapped, removed, or added. An added benefit of bite-sized content is that agents can take away quick learnings without a huge time investment, and training can easily be done in small windows during idle times when there’s a lull in call volume.

In the call center environment, adaptive learning tools work especially well when they’re integrated with quality monitoring tools, with everything consolidated into one platform. When an employee fails a quality check on a transaction, then their team leader can seamlessly assign training that will prevent similar failures from happening in the future. Training will naturally be more efficient because of adaptive learning practices. And when team leaders don’t have to switch tools or go through any convoluted processes, then the assignment of training is more efficient too.

None of this can work without a powerful adaptive engine. An engine like Heyware provides all the algorithms, assessments, and adjustments needed to provide the adaptive learning that increases training efficiency and effectiveness, reduces unconscious incompetence, and sets your team up for success and increase CSAT or customer satisfaction.


Want to learn more?

Download our e-book, Beyond Co-listening  - 9 fasttrack steps towards a killer CMX program, for even more in-depth advice about starting a quality program or look at how Heyware's industry leading Adaptive Learning Platform can help you achieve higher quality within your contact center.