Contact centers are complex and unique businesses. Some are five agents strong while others employ thousands. And while each contact center has its own business strategy and objectives, one common goal spans the industry: keeping customers happy.
In a service-based economy, positive customer interaction is more important than ever. According to a Blackhawk Network study, 94% of customers say that a consistently great customer experience is the main reason they stay loyal to a business or brand.
And while agents may not consider themselves brand ambassadors, the interactions they have with customers, employees and partners often determine a brand’s reputation.
With that in mind, those on the front lines must be trained and ready to go. There are many options for agent development, including in-house and external training, but one of the most effective practices for training agents is to gain insight into their everyday behaviors and use this information to improve interactions on an ongoing basis. A key way to achieve this is by using automated contact center analytics.
Analytics and reporting are designed to reveal the why, not the what, of agent interaction—turning quantitative figures into qualitative solutions. When contact center managers use advanced insights to determine why an interaction happened the way it did, it provides an opportunity to bolster agent training and improve the next customer interaction.
Revealing and Supporting Where Agents Struggle
Automated analytics software can give contact center managers a complete picture of a customer interaction by looking at patterns in speech, desktop and text interactions.
From a training perspective, this allows large quantities of data to be used to pinpoint specific areas where agent behavior is having a positive or a negative impact on customer interactions. Areas of improvement can be identified, and data on positive interactions or behavior can provide a helpful example for agents as they continue to learn.
One area where agents tend to struggle is with high stress, emotional callers. Using voice-of-customer (and employee) analytics is one way companies can measure whether this is the case for their own agent employees. Analytics and the resulting insights can reveal the exact point in high stress, emotional conversations where an agent might need assistance.
This gives supervisors clarity into situations where they are (or should be) getting calls directed to them. In addition, analytics can identify specific agents that struggle with emotional callers. This allows managers to implement targeted assistance and training—leading to improved customer interactions and better trained agents.
Uncovering Opportunities for Advanced Training
Automated analytics are highly beneficial for solving problems that could impact customer or agent satisfaction, but analytics can also be used to uncover proactive training opportunities. They can illuminate trends that appear in agent interactions so company leaders can use these trends to identify areas where agents have knowledge gaps.
For example, analytics might identify a correlation between the use of negative phrases like, “I don’t know,” and calls that are placed on hold. When leaders dig into the data and situation, they discover that calls placed on hold—and negative phrases—spiked when company leaders deployed a new knowledge base. Without analytics, the team would not have been able to make that connection, further degrading both customer and agent experiences.
Once a trend is identified, a knowledge gap can be filled. This allows companies to take insights and institute targeted training in the needed areas. By using insights from analytics, companies can pinpoint the specific areas where agents need help and address those knowledge gaps quickly and specifically. Why spend the time and resources on a broad, expensive training when a pointed, in-depth seminar would be better?
Unexpected situations can also trigger a need for extra training. But without analytics offering insight on changes, leaders often do not know where to start.
The COVID-19 pandemic changed life and work for many people, including contact center agents. Millions of agents across the world shifted to a work-from-home model, some literally overnight.
Organizations using analytics were able to quickly identify impacts on interactions and behaviors, as well as track how agents were functioning during this time of crisis. For example, KPIs might indicate longer-than-usual call-resolution times. But analytics show that agents are dealing with customers who are scared, sad or confused, causing agents to modify their behaviors and spend additional time reassuring customers and working through fewer calls.
Building a Culture of CX Improvement
The best athletes, teachers and writers continually work on improving their technique, and the same is true for customer service professionals. Analytics should not only be used to identify weaknesses but to create a continuous culture of improvement. And the most important area to identify that improvement in is in customer experience. The trends that analytics identify can be used to train CX-savvy agents.
By using sentiment analysis, contact centers can analyze customer tone and track how satisfied customers are with their voice or text interactions. These insights can then lead contact centers to find ways that agents could improve the customer experience.
One direct way that agents can improve the customer experience is through their language selection. Whether it be through spoken or written exchanges, the customer experience is directly affected by the conciseness and clarity of an agent’s words—but also the actual words agents choose to use.
Speech-to-text transcription, in conjunction with sentiment analysis, can reveal places where a customer exchange went well or poorly—allowing for real-time training opportunities. However, a creating a culture of CX excellence requires outside-the-box thinking. By using analytics, companies will have the insights needed to understand how their customer interactions are going and develop ways to make them more positive.
Sentiment analysis can identify strategies to improve the customer experience in very specific ways. For example, speech and text analytics can identify “powerless to help” language and phrases like “not allowed,” “unfortunately” and “I wish we could” in customer interactions.
This type of language is often tied to low sentiment scores and negative customer feedback. By understanding where and when this is happening, leaders can work to remove those phrases from their agent’s vocabulary.
Improving the Agent Experience
In the past, analytics-based insights have been criticized for being micro-managerial or negative toward the agent experience—but modern analytics are designed to be pro-agent, offering an opportunity to help agents create better experiences for their customers and themselves.
As with all workers, contact center agents have their natural strengths and weaknesses. While analytics should be used to train agents in the areas where they could use improvement, they can also be used to reduce tension by sorting calls.
Companies can use the insights delivered by analytics to determine calls that should be placed to certain agents and not to others. By creating a tiered system like this, companies can reduce the stress on agents by putting the right agent on the right call.
Bluegrass Cellular instituted a similar strategy and saw a benefit to customers by allowing higher-level issues to be dealt with sooner.
Just like sentiment analysis can be used on behalf of customers, a manager can also use sentiment analysis to keep agents more productive and happier. If insights determine that a certain group of agents have been experiencing a high level of emotionally stressful calls, contact center managers can use this to inform training strategies and scheduling to ensure agents are not overworked or burned out.
While training is about improvement, it is also about acknowledging existing strengths. Analytics can work on behalf of agents to identify opportunities for kudos. One contact center took this to heart when its analytics revealed that internal perceptions around short calls were not always true.
After using speech and text analytics on calls of one minute or less, this contact center determined that many of their short calls were actually agents who were going above and beyond in their job to place follow-up calls to customers who had expressed earlier frustration with the company. This agent action resulted in grateful customers and the contact center used these interactions to create best practices moving forward.
No two customer interactions are the same, but with insights delivered from analytics, contact centers can create informed training programs that keep agents ready to succeed in any environment. An analytics-based training program can reveal opportunities for agent growth, identify new contact center strategies, and keep customers and agents happy.
