Call Center Analytics

Agent churn: It’s not you, it’s your employee engagement strategy

Jeff Gallino, CTO and founder of CallMiner

It’s no secret that contact centers are infamous for their high turnover rates, which average 45 percent year-over-year—more than double the average for all U.S. occupations. What most companies don’t realize, however, is that this doesn’t have to be the status quo. Identifying the signs an agent is about to check out and having solutions in place to change the outcome can dramatically reduce agent churn well before they decide to give their notice.

If retention isn’t motivation enough, research shows that an astonishing 77 percent of employees worldwide are not engaged, which, according to Gallup, can cost upwards of $605 billion in lost productivity per year. There’s incredible value in spotting non-engagement signs and addressing the lack of productivity that often lead to agent turnover early. This can ensure strong employee engagement and stop the turnover cycle. Not only will it save billions in lost revenue, it will promote better customer experiences through an organization’s No. 1 advocate—its employees.

Warning Sign 1: They go into silent mode

One of the primary indicators of an unengaged employee is silence. Silence is commonly caused by a lack of agent training, but this isn’t only applicable immediately after onboarding. Agents require extensive knowledge of your company’s products and services; however, many employees miss out on new product information because organizations neglect to offer continual education programs.

Employee silence can also happen outside of customer interactions, as managers of unengaged agents tend to notice an increase in the amount of time between each call. Although this doesn’t usually stem from a lack of company knowledge, it’s a telltale sign an employee is experiencing a lack of motivation. Distant employees are comfortable with doing the bare minimum to get by and will likely keep their heads down, and calls quietly recording, to purposely limit the number of customers they interact with.

Warning Sign 2: Under (but not terrible) performance

Decreased performance in areas such as average handle time (AHT), call volume, and following a script could all point to a lack of engagement that, if not fairly addressed, can lead to lower NPS scores, turnover, and even compliance risks.

Sometimes, however, quantifiable performance metrics aren’t the sole indicator of an agent’s performance—as agents aren’t at-fault for many of the disruptions that happen during the call. Companies need to take training, tools and technical factors into consideration when it comes to gaps in an agent’s performance and use contextualized scoring methods to accurately and thoroughly understand where performance issues are occurring and the root cause.
Warning Sign 3: Inconsistent feedback on their work

According to research by Gallup, less than 21 percent of employees strongly agree their employee implements fair evaluation processes. Contact center agents handle dozens of calls per day, but many outbound surveys and manual quality management reviews only account for three to five percent of an agent’s interactions—leading to ill-informed assessments of their overall performance.

In addition to being inaccurate and irregular, many legacy feedback systems are impersonal. Call center feedback usually only involves reprimanding, despite the employee’s desire to be recognized for exceptional service. The lack of effort put into celebrating successes usually causes agents to feel unappreciated and less likely to advocate for the business.

How to Stop the Cycle

Proper training—during and after onboarding: Before sending your agent out on their own, how do you know you’ve given them the proper training to handle the influx of problems they’ll face out on the floor? To keep up with the fast-paced environment of the contact center, they need to stay informed, especially if your products and services are constantly evolving. Each one of your employees is unique and despite what’s suggested by legacy employee education programs—their training processes should be as well. Speech analytics data can help managers offer personalized training programs in accordance with agents’ specific needs, even after onboarding.

Tools to optimize performance: Aside from training, contact center operators need to ask themselves whether their agents have the resources they need to succeed. While two-thirds of customers dial in with a problem, some caused by lack of self-serving options on other channels, they expect your agent to be able to solve, lack of resources is one of the biggest factors leading to job-related stress. It’s impossible to guide each of your representatives through every single interaction—but tools and customer engagement analytics software can take information in real time and apply historical data to provide your agent with better insight and guide them through the call based on the context of the conversation.

Real-time feedback: Agents should always know where they stand when it comes to their performance. A discussion a week, a month, or a year later about a specific interaction with a customer will not help anyone succeed. Having an analytics tool removes any sense of unfairness that’s usually associated with random selection by providing an inclusive and holistic view of your caller engagement data, ensuring a stronger voice of your employee. It also helps with coaching by automatically scoring 100 percent of your agents’ customer interactions to pinpoint the exact areas they need to both improve customer experiences in real-time and add business value in the long run.

While employee turnover is one of the biggest problems companies face today, employee engagement is just as impactful to your business’s bottom line, as those with highly-engaged workforces outperform their peers by nearly 150 percent. All problems associated with the warning signs of an unengaged employee point to a similar source—the company’s inability to fully understand the needs of their employees from both a personal and professional perspective. Similar to how analytics and artificial intelligence work to strengthen customer loyalty, these tools and concepts can help personalize your organization’s approach to agent management—offering a fully-developed employee engagement strategy that involves critical coaching and feedback procedures. In doing so, companies can foster a positive work culture and keep employees from feeling as though they are ‘just another number’.

Important Business Intelligence Tools for the Contact Center

In order for the contact center to meet (and exceed) performance goals, the right business intelligence (BI) tools and technologies have to be in place. BI tools help contact centers improve and optimize their processes in order to heighten their success rate. BI digs deeper into the data you’re already collecting to find ways to relate your findings to the customer experience and, in turn, improve customer retention.

Aggregate Analytics

Aggregate analytics, also referred to as big data, deliver information about the contact center’s overall performance. Both structured and unstructured data is organized and delivered via an “at a glance” dashboard, or something similar. The key is to have only relevant data included so that supervisors don’t have to wade through inapplicable data.

Call Recording Tools

Speech analytics tools – a long-time staple of the modern contact center – accurately transcribe conversation audio to ensure that agents are adhering to a script or guidelines when speaking with a customer. In industries that have strict rules about what can and cannot be mentioned (like collections, for example), speech analytics are even more important than usual. Certain advanced call recording tools will allow for Voice of Customer considerations, too. Real-time feedback, call coaching and customer surveys enable supervisors to make decisions that can improve the customer experience in-the-moment.

Predictive Voice Analytics

Predictive voice programs not only record agent-customer conversations, but also use them to make predictions about how both parties will respond. Emotional changes in the agent’s vocal features can determine if the agent is speaking in an appropriate way to the customer, while emotional changes in the customer’s voice can determine a variety of outcomes, like if they’re likely to become a regular customer.

Selling Recommendations

BI tools can increase revenue by recommending up-sell and cross-sell opportunities to the agent in real-time. By considering the customer’s purchase history and buyer persona, combined with predictive voice analytics, the dashboard can alert the agent when a selling opportunity presents itself. Not only is it easier to sell to customers with a strong purchase history, but BI tools can also determine which products and services will be of most interest to the customer.

The contact center is generating helpful information every single minute. Data is regularly being collected, sometimes passively. With BI tools, supervisors can gather and review all pertinent data to see where improvements can be made.

5 Tips for Root Cause Analysis in the Contact Center

The best way to solve a problem is to dig deep and find out where it started in the first place. Often, what you see of a problem is a symptom, not the cause. Here are five steps you can take to improve your contact center’s root cause analysis.

  1. Consider acoustic issues.

Root-cause analysis should take acoustic factors into account. For example, if the call has long periods of silence, this could point to a problem with the system. If the contact center agent can’t access data quickly enough or if there are problems with IVR, a slow system may be the problem.

  1. Flag conversations that are abnormally long.

Speech analytics will let you sort through calls based on parameters like duration and repeated calls. You can also find calls where specific keywords are mentioned, like those that are normally associated with a complaint. This will let you know which calls need the most attention.

  1. Monitor data in real time.

Accessing real time data can help you spot and stop issues early. If a new sales or marketing strategy launches and then phone calls start coming in within an hour or two, you’ll know that there’s a problem with the launch that must be fixed. Real time data lets you identify trends as they emerge, giving you the opportunity to stop a problem in its tracks.

  1. Sort problems into categories.

As you start to uncover the main problems customers are having, you can segment them into categories, such as product defects, customer education and marketing communication. Then, you can meet with specific teams to come up with targeted strategies to solve the problems.

  1. Understand the context of the situation.

Relying on word count frequency isn’t enough – the terms and phrases that are being used have to be understood contextually, too. Knowing the context of a problem instead of just the hard data will allow you to pinpoint the situation that caused or contributed to it.

Knowing the average number of complaints your contact center receives on a weekly basis is just a start. You have to figure out the root cause of the complaints in order to effectively tackle them and prevent them in the future. Root cause analysis is a way to solve prominent issues instead of merely putting a Band Aid on them.

4 Important Categories of Contact Center Analytics

 

Contact centers collect a lot of data. They can find out what their customers are doing on a daily basis. They can determine what time a customer contacted support and how long their contact lasted. They can listen carefully to conversations and decide if a customer is happy or angry based on certain keywords. All of this data helps the contact center do things like reduce call times and examine agent performance. To be competitive, contact centers have to stay focused on the customer. By keeping track of customer service metrics, contact centers can make decisions based on reliable data.

  1. Speech Analytics

Speech analytics help contact centers improve a customer’s phone call experience. Customer service agents are monitored to ensure they’re adhering to scripts and following regulations. This can also pinpoint the areas in which an agent needs additional training. Speech analytics will also segment hard-to-handle calls so that they can be dealt with by a supervisor or an agent with more experience. Furthermore, speech analytics can determine the reason for the customer’s call, what they hope to get out of the call, and if they are happy, upset, stressed, satisfied, etc.

  1. Interactive Voice Response (IVR) Analytics

Intuitive IVR systems improve the customer experience. Insights that can be gleaned from IVR analytics include the percentage of callers who want to speak with a live agent and their reason for doing so; the reason for the transfer of calls between departments; the percentage of callers who were not identified accurately; and the number of calls that were handled from start to finish by IVR.

  1. Overall Customer Satisfaction

Gauging overall customer satisfaction will give you an idea of how well you’re delivering the entire customer experience. In order to measure customer satisfaction, the CSAT score is often used. The contact center will ask the customer to rate their satisfaction with a specific experience, like an interaction with the company or a transaction. For example, the customer may be asked to rate their satisfaction on a scale of one to ten. Any answer that’s a six or above means the customer is satisfied. To figure out the percentage of satisfied customers, the number of customers who responded with a satisfied rating is divided by the total number of customers who were surveyed.

  1. Predictive Analytics

Tracking analytics isn’t worth much if you’re not going to take the information and figure out how to improve the contact center. Predictive analytics show the changes that will most impact the performance of the contact center. Management can then figure out the best way to communicate with customers, retain happy customers and resolve problems with dissatisfied customers.

One single metric will not give you a useful view of customer service quality. Instead, several metrics that are carefully chosen based on your customer service goals have to be followed. Tracking analytics allows the contact center to improve, update and revamp their programs on a regular basis.