How to improve CSAT scores in your call center

“We pick companies because of their products, but we often leave them because of their service failures,” according to the authors of The Effortless Experience. No pressure on your call center, right?

Your call center is responsible for assisting customers who often feel inconvenienced, frustrated, or angry. The goal is to leave the customer satisfied so they’ll want to keep buying from your business. Most call centers measure their success using an overall CSAT (customer satisfaction) score.

CSAT is more than just a vanity metric. Research shows that high customer satisfaction leads to higher customer retention, higher customer lifetime value, and a stronger brand reputation. It’s the North Star for many call centers.

But how do you improve your CSAT score when dealing with customers who probably didn’t want to contact your call center in the first place?

It starts with understanding the agent behaviors, processes, and customer journey pain points impacting satisfaction. 

First things first: How to measure CSAT

If you’re looking for advice on improving CSAT scores in your call center, chances are good you already have a firm grasp on what CSAT is measuring. You probably also have a system in place to measure CSAT, and if you’re like most call centers, it’s survey-based.

Post-interaction surveys have been the go-to method for measuring CSAT for decades. A customer calls your company, and after an agent assists them, they ask the customer to stay on the line to complete a survey (or your company sends an automated survey over email or SMS). This survey typically asks the customer to rate their satisfaction on a 1-5 or 1-10 scale, and your company compiles the results to get an overall CSAT score. 

But surveys don’t tell you the full CSAT story. For one thing, only a small percentage of customers fill out surveys (about 6-8% on average). And the customers most likely to complete a survey are the ones who had either an excellent or terrible experience with your business–meaning you’re not hearing from the vast majority of customers who fall somewhere in the middle. 

Thanks to the emergence of AI-powered conversation intelligence software, it’s now possible to get a CSAT score for every customer conversation without relying on surveys. This technology uses machine learning models to predict a CSAT score based on what the customer and agent said in their conversation. This gives you a more representative view of the CSAT metric. It also lets you evaluate trends in your conversation data–related to agent behaviors, call reasons, pain points, and more–to understand the biggest factors impacting customer satisfaction.

Understanding what causes your customers to feel satisfied or dissatisfied is the key to improving CSAT scores in your call center. Once you understand those factors, you can take targeted actions to address them. 

Below, we’ll look at several strategies to uncover and address the causes of dissatisfaction in your call center interactions.  

Understand and coach the agent behaviors impacting CSAT

How your agents treat your customers has a huge impact on customer satisfaction–and whether customers continue doing business with you. The top three reasons customers report coming back to a business all have to do with how employees treated them in service interactions (the agent was 1.) helpful, 2.) knowledgeable, and 3.) friendly).

Simply telling your agents to be more helpful, knowledgeable, and friendly isn’t useful, but you can analyze specific behaviors across their calls to identify targeted areas where they need additional training. Some of the biggest opportunities for improvement we’ve uncovered in our research include:

• Advocacy: Tethr’s State of CX study found advocacy language has a bigger positive impact on the customer experience than any other agent behavior. Agents should avoid powerless-to-help language and focus on what they can do.
• Expectation setting: Our research found that missed expectations were the most common reason customers expressed frustration. Work with agents on the language they should use to set proper expectations (and include this language in your scripts). Make sure you also have the right processes in place to ensure any necessary follow-ups happen (e.g., if the customer requests a follow-up call with a status update, does the agent create a task in your CRM?).
• Avoiding being overly apologetic: Our research showed that the more times an agent apologizes without offering a solution, the higher the customer perceives their level of effort. This finding confirms earlier research from Zendesk that found when “sorry” is repeated in a conversation, it leads to lower CSAT scores. While agents should be polite and friendly, they should focus on explaining the steps they’re taking to resolve the issue instead of repeatedly apologizing.

Tackle the factors driving up handle times

Customers expect fast service: 60% think waiting on hold for even a minute is too long. And while the time customers spend talking with an agent will depend on their specific issue, customers can quickly grow frustrated by long stretches of silent time or the agent stalling to look up information.

Reducing average handle time (AHT) shouldn’t be your contact center’s sole operational focus (again, some complex issues take longer to resolve). However, looking at calls with long handle times can help you identify potential process issues or areas where agents need additional training. You can use conversation intelligence software, such as Tethr, to isolate calls with long handle times and look for trends in topics discussed, agent behaviors, and other factors. With Tethr, you can even conduct a root cause analysis to determine which factors directly impact your average handle time.

Once you find a controllable factor that’s unnecessarily driving up handle time, you’ll need to come up with a plan to address it. For example, are handle times long because your agents have to navigate between multiple systems to find the information they need? You could implement a real-time agent guidance platform that brings workflow steps and all relevant data into a single interface.  

Addressing the factors inflating your handle times can help reduce operational costs and increase customer satisfaction–a win-win for your contact center.

Listen for mentions of friction points in the customer journey

Unfortunately, customers may be dissatisfied by the time they contact your call center. According to The Effortless Experience, any customer service interaction is four times more likely to cause disloyalty than loyalty.

Of course, your call center has the power to turn your customer’s experience around and leave them satisfied by efficiently resolving their issue. But what if you could also use insights from your customer conversations to identify product issues or friction points occurring before the customer contacts you? 

This is another scenario in which conversation intelligence technology can help. You can easily track and categorize mentions of specific product issues or sources of customer effort, such as the customer mentioning they tried to find a solution on your website before calling. Prioritize the issues mentioned in the most calls and share your data with the team or department leaders who can address the problems. 

By working cross-functionally to address common custom issues, you can reduce call volume and customer effort, leading to higher overall customer satisfaction.

Final takeaways

Your call center’s CSAT score shouldn’t be a mysterious metric, moving up or down without a clear cause. Analyzing your customer conversation data with AI lets you identify the specific factors impacting customer satisfaction. And once you know what controllable factors are impacting your CSAT scores, you can take a targeted approach to CSAT improvement, rather than just relying on a handful of verbatims from your surveys. Conversation intelligence gives you an efficient way to increase your CSAT score while removing points of friction, leading to a better experience for your call center team and customers.