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Your least happy customers might be your most valuable customers—if you get the right data. Hear us out.
If you’re in the customer experience industry, you know customer satisfaction (CSAT) data is one of the most popular KPIs. But you might overlook customer dissatisfaction (DSAT) data when you look at customer satisfaction levels.
Digging into negative customer experiences isn’t the most fun exercise, but it pays dividends in the long run (and when it comes to customer retention). In this article, you’ll learn five steps to turn negative customer experiences into a goldmine of data you can use to elevate your brand and maximize your support agents’ potential.
Customer dissatisfaction (DSAT) is derived from CSAT survey responses. Here’s a quick refresher, in case you need it:
Brands send CSAT surveys after customer service interactions. They include one simple question: “On a scale of 1-5, how satisfied are you with the support you received today?” 1 means “extremely dissatisfied,” while 5 means “extremely satisfied.”
Any response labeled as 1 or 2 falls into the DSAT category.
If you don’t already, include a free-form text box below your CSAT survey where customers can explain why they gave the score they did. This is crucial for a DSAT analysis (more on this soon).
Once the DSAT tickets are compiled, they can be tagged based on why the customer was dissatisfied. There are three main DSAT categories that often come up:
This refers to complaints about agent inefficiency, lack of product knowledge, escalation procedures, etc. It also includes frustration with long hold times or having to reach out multiple times to resolve an issue.
If a customer’s issue stems from a defect, bug, missing/broken part, etc., it falls into this category.
Customers might reflect a bad experience with a product or service in their CSAT response—no matter how friendly or efficient the agent is. These types of issues are rarely under the agent’s control, but they still yield valuable feedback to pass along to other departments, such as the product team.
It’s common for customers to get frustrated with company-wide rules and regulations. This includes return, exchange, and refund policies, hours of operation, or other policies that fall outside the CX department’s control.
A round of Quality Assurance (QA) audits adds additional context to DSAT tickets, namely the ones that involve customer support processes.
A QA audit involves reviewing a customer-agent interaction to determine how well the agent performed and adhered to the brand’s standards. Depending on your volume of DSAT tickets, a QA analyst or CX leader can audit every ticket or a sample. The more data you collect, the more accurate your insights will be.
Every QA audit starts with a QA scorecard. This is a rubric based on a company’s values and standards for agent-customer interactions. QA scorecards are a roadmap for agents to sharpen their skills; they provide measurable metrics that impact customer satisfaction and customer loyalty.
Here’s an example of what a QA scorecard looks like:
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Put simply, DSAT data alone tells you if customers are unhappy. But QA audits tell you why.
QA audits aren’t the only way to identify the underlying cause(s) of dissatisfied customers. Let’s look at two root cause analysis (RCA) methods that are beneficial for CX teams.
A fishbone diagram (also called a fishbone analysis) is a visual representation of cause and effect. The problem is listed at the “head of the fish,” and the potential causes are listed on the “bones” of the fish in varying categories or areas.
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Here’s a brief example in the context of CX:
The main benefit of the fishbone diagram is that it keeps the focus on the causes of problems rather than symptoms.
As the name implies, the 5 Whys Technique involves asking “Why?” five times when you encounter a problem. This might sound simplistic, but it can uncover unexpected insights.
Let’s say a customer indicated they were “very unsatisfied” in their CSAT scores. Here’s a 5 Whys sequence that might follow:
Just like the fishbone diagram, this technique keeps you focused on the essence of the problem instead of surface-level observations.
Once you get a firm grasp of the support- and non-support-related issues leading to DSAT, put those key learnings to use. Here are four types of changes CX teams can implement with DSAT data:
Get ahead of customer complaints by training new agents on red flags to look out for. Some teams have to learn lessons the hard way first, but documenting those experiences prevents newer agents from running into the same issues down the road.
This can range from product knowledge to specific language that resonates well with your audience.
Let’s say through QA audits you discover agents are asking customers for information that’s already available in your CRM, leading to unnecessary customer effort. In this case, you’d tailor coaching sessions to teach agents how to track down past customer conversations in your CRM so they can get that information on their own moving forward.
The more your coaching sessions are informed by fresh data, the more impactful they are.
DSAT insights don’t do any good sitting around collecting digital dust. This is an opportunity to create or expand a living, breathing resource for agents.
Consider the ride-sharing app Lyft, which struggled to formalize knowledge for its CX teams. For example, agents were unsure what types of vouchers they should offer to customers, which backed up their queue.
MaestroQA helped them implement a knowledge base in tandem with a QA program. The result? Lyft’s senior agents were freed up to focus on the tickets in their queue, reducing their Average Handle Time and improving agent productivity.
If DSAT stems from an issue outside the CX team’s control, don’t ignore it. It’s important to share your insights with other departments, especially since CX teams are on the front lines interacting with customers every day.
This includes suggestions for user experience (UX), product design, billing policies, shipping, and other ways to drive customer loyalty.
Learning about why customers are unhappy can be disheartening for customer support organizations to study. As a result, companies often ignore DSAT data, and only pay attention to CSAT data from satisfied customers. Or they collect it but don’t act on it. But as you can see, digging into DSAT measures is an effective way to identify and improve your company’s weakest links. By following the steps above, your DSAT analysis will pave the path for elevated agent performance, happier customers, and improved customer loyalty.
Want to start uncovering more actionable CX insights? Request a demo of MaestroQA today.
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