By Brad Snedeker
As a business process outsourcer (BPO) or outsourcing contact center, your agents serve as the face of your clients’ businesses. Low performance and high agent turnover can have a negative impact on the overall business. This can manifest in reduced end-customer loyalty and satisfaction.
Even in the best of times, high-quality agent training and assessment presents challenges. In 2020, with a sudden shift to agents working from home due to the pandemic, the emphasis on proper training, monitoring, and assessment has become even more critical. This applies not only to new agents joining your organization, but also to existing agents who may be taking on new roles, new clients, or new channels.
Automating Data Science for Improved Interactions
One traditional way of teaching agents how to interact with customers has been to shadow a top-performing agent. But job shadowing has its limitations. It’s difficult to learn how to respond to different customer needs, the trainer agent might act differently when the trainee watching, and the trainee has limited time to learn and ask questions. Even so, shadowing can be helpful for agents to get a high-level feel for the tone and language they should emulate. But training shouldn’t end there.
Today, contact centers can leverage software automation to record and analyze agent interactions over the phone, email, chat, and social media. Centers can also use this information in near real-time to enable virtual or on-site management insights and training inspiration. This approach to training offers a richer experience and helps build agent confidence. It also makes training more efficient since you’re not asking other agents or managers to listen to and respond to every scenario or question.
Interaction monitoring, recording, and analytics together can reveal the why, not just the what, of agent performance, allowing managers to uncover trends and improve interactions for better long-term outcomes. It offers an opportunity to improve training for specific agents and enhance the customer experience for future interactions.
Uncovering Best and Not-So-Best Practices
Using massive quantities of data and automated analytics to uncover specific areas where agent behavior is impacting a customer interaction can shed light on experiences both positive and negative. This shows agents specific areas where they can improve, as well as find examples of behavior or language that other agents can emulate. A well-provisioned quality management system can even allow a contact center to share best practices with the click of a button, creating a library of successful examples.
For instance, one contact center manager discovered that an increasing number of retail customer calls escalated from first-contact agents to a supervisor. This diverted the supervisor’s attention away from other aspects of the business and hindered unrelated KPIs.
Voice-of-the-customer (and employee) analytics allowed the team to isolate relevant interactions based on this pattern of escalation and apply speech analysis. The analysis revealed the exact point in the conversations where the agents needed supervisor assistance. This level of insight gave the retailer the why for agents who struggled to manage challenging and emotional calls.
Using analytics, the managers identified the agents who grappled with this type of interaction. This allowed them to implement targeted training and assistance, creating a new best practice for all agents.
Not only was this beneficial for the retail brand’s reputation with customers, it also helped agents improve their skill sets and learn how to de-escalate situations by modifying how agents interacted with customers. Reducing the stress of interactions had the additional benefit of creating happier, more successful agents who were less likely to turn over.
When Change Dictates New Training
Through automated analytics, contact centers can also uncover training opportunities due to changes in their own processes.
For example, using speech analytics as part of its normal quality control efforts, one contact center identified a correlation between the use of phrases like “I don’t know” and calls placed on hold. Further, managers found a pattern in which calls placed on hold spiked when leaders deployed a new knowledge base. The company had inadvertently introduced its own problem. The analysis helped leaders quickly institute training in the areas where agents had knowledge gaps when new tasks were added, avoiding any long-term impact.
Unexpected situations can also trigger a need for extra training, but without analytics offering insight on changes and the new landscape of operations, leaders often don’t know where to start.
According to a Calabrio study, 89 percent of contact centers had at least half their agents shift to a work-from-home model due to the pandemic. This compares to only 36 percent of contact centers with half their agents working remotely pre-pandemic.
Contact centers using analytics can stay close to their teams and quickly identify impacts on interactions and behaviors for new remote agents, as well as track how agents are functioning during this time of crisis. For example, KPIs might have indicated longer-than-usual call-resolution times. However, live interaction monitoring and analytics showed that agents were dealing with more customers who were scared, sad, or confused.
This caused agents to modify their behaviors and spend additional time reassuring callers and working through fewer calls. New training, then, placed the emphasis on easy displays of empathy and ways to navigate complex interactions rather than on speed and low handle times.
Creating a Culture of CX Excellence
In addition to identifying weaknesses, centers can tap analytics to create a continuous culture of improvement. One area where this is especially important is with the customer experience (CX). Customer expectations will become more demanding in the future. In fact, 69 percent of contact center managers expect customers to have an increased need for emotional empathy in customer service interactions post-pandemic. Analytics can be a tool to support agents as customer needs evolve.
For example, sentiment analysis can help contact centers analyze customer and agent tone, as well as track how satisfied customers are based on their voice or text interactions. Radial, a BPO serving leading retail brands, used sentiment analysis to identify strategies to improve its end customers’ experience.
Using speech and text analytics, Radial identified instances of powerless-to-help language and phrases like “not allowed,” “unfortunately,” and “I wish we could” in customer interactions. Leaders correlated those to negative-sentiment scores. The results allowed Radial to create training and strategies to empower agents with the right tools, resources, and language to improve interactions and reduce negative-sentiment scores.
Simply by understanding the correlation between specific language and sentiment, Radial increased its net first-contact resolution by 3 percent, increased net customer satisfaction (CSAT) by 2.1 percent, and improved net agent demeanor by .56 percent.
Not Just for the Customer
In the past, analytics-based insights had the stigma of being micro-managerial or critical toward agents. However, modern analytics use is meant to be pro-agent, offering support when needed and credit when deserved. By leveraging workforce engagement management tools together—including recording, quality management, workforce management, analytics, and reporting—contact centers now have the technologies they need to understand the details behind the good and the not-so-good customer-agent interactions. With this knowledge now easily accessible, applying training to make each interaction a positive one has the potential to improve every aspect of contact center work.
With more than fifteen years in the industry, Brad Snedeker has extensive knowledge of the contact center space. As Calabrio’s director of innovation, he ensures that customers have access to the best training available. He works directly with users to develop new and innovative techniques to implement workforce optimization best practices.