A customer support team isn’t ready to be the point of contact between customers and your brand until they have the right tools for the job. The most effective tools come in the form of customer service metrics—actionable data that offers a clear picture of your team. This includes factors such as work volume, team efficiency, and customer-support effectiveness. Tracking customer service with the wrong metrics isn’t just foolhardy—it’s self-destructive.
Choosing customer service metrics is a subtle art. It’s not quantity, but quality that matters. Looking at too many metrics muddies the waters and further obscures any existing CS problems. But selecting the right ones will pinpoint problem areas and clue you into exactly which customer interactions require your attention. Moreover, focusing on these relevant metrics will help scale personalized support as your business grows while at the same time keeping costs down.
The first step in identifying which metrics to utilize is considering their place in the customer journey. To do this you need to start thinking of the effort that you are putting your customers through at each step of the journey.
When customers exert a high effort to resolve issues, it results in 96% customer disloyalty. And you can bet that failing to identify these negative interactions will lead to your customer churn rate launching into the stratosphere. The solution is to focus on two scales:
- the interaction value scale
- the effort scale
The rule of thumb is that low-value customer interactions should require little effort, while high-value interactions improve the customer’s perception of your business.
Low-value interactions include invoicing, updating billing info, or other things that customers generally consider a hassle. Automation and self-service go a long way to helping your customers exert as little effort as possible, thus keeping them content.
Conversely, turning high-effort customer interactions into high-value ones means implementing strategies like training classes and software, webinars, in-person meetings and personalized support. While developing these strategies comes at a cost, if you do automation right on the low-value end, you should save enough cash to implement the high-value strategies in a cost-effective way. See the chart below:
Now that we’ve identified how customers interact with your business, it’s time to select the metrics and the training tracking software to measure your progress.
The Right Customer Metrics
Whether your product or service has failed, met, or surpassed customer expectations is a fundamental question. Customer Satisfaction (CSAT) is a time-honored metric used to glean this insight. CSAT got its start back in the 1940s when radio programmers realized they could measure audience engagement, and thus the ratings index was born.
CSAT has evolved over the years, but even today its core question is: “How do you feel about your most recent interaction with the company?”
You can modify this by asking such things as “How satisfied are you with the service?” or, “How would you rate your overall experience?”
Help desks send these customer satisfaction surveys in a variety of ways, from offering just two options for answers (good and bad) to utilizing a Likert (agree/disagree) scale. The main benefits of this metric are its ease of use (usually a one-click setup) and its straightforwardness—it’s simple for customers to understand. The drawback is that a positive CSAT doesn’t necessarily correlate to increased loyalty and sales.
Customer Effort Score
Like CSAT, the Customer Effort Score is typically one you want on your radar. This metric, created by CEB Global in 2008, quantifies how much effort a customer puts into their interactions with your brand. It’s a solid indicator of loyalty and customer satisfaction.
However, the first iteration of the CES metric wasn’t without its flaws. The question asked customers to rate the effort they put forth on an inverted scale of 1 (low effort) to 5 (very high effort). In CES 2.0, the question was reframed on the Likert scale by saying: “To what extent do you agree with the following statement: the company made it easy for me to handle my issue?”
The second CES metric, with this specific wording, proved to be 25% more predictive of customer loyalty than previous versions. This means the CES has become one of the most valuable metrics for any business.
Net Promoter Score
Net Promoter Score (NPS) serves one major purpose: to determine a customer’s future behavior. A single question gleans this info: “How likely is it that you would recommend our product/service/company to a friend of colleague?” Customers respond on a scale of 1 (very unlikely) to 10 (very likely).
NPS is highly efficient at identifying detractors (those who answer lower than 6) and promoters (those who answer 9 or higher). Those who answer in the 7-8 range are called “passives.” High scores correlate to increased growth in the form of referrals and repurchases, while low scores correlate to a higher customer churn and poor reviews.
The principal benefit of NPS is that it addresses the entire customer experience and is effective at capturing holistic opinions. Many departments, from the marketing offices to the product floor, can implement the results it provides.
Measuring volume is crucial when examining customer interactions. Total Conversations is a metric that shows all new support requests during a given period of time. Each conversation includes the initial inquiry as well as all subsequent replies.
Best managed through a help-desk app or a call center sales training software, tracking this metric will clue a business into how efficiently their support team operates. It highlights support trends and, when viewed over time, will tell a business when it’s time to bring fresh blood into the support team.
One drawback to Total Conversations is that often the help-desk app in question will count as conversations those items that don’t require a reply, such as auto-respond emails or Twitter mentions. This only clutters support inboxes, so team members need to look closely at each conversation.
This is another volume metric that follows with Total Conversations. However, Total Replies differs in that it ignores the conversation thread in favor of tracking individual replies in a given timeframe.
This gives businesses a good idea of just how much heavy lifting their support team is doing in the form of sending responses to customer requests. That said, it isn’t a good predictor of efficiency, as a high number of replies doesn’t always translate to better support service. If a problem can be solved in one or two replies, that means the rep sending five or six replies is providing a worse customer experience.
A comprehensive list of these and other metrics can be found at Kayako. Remember, the goal isn’t to aggregate as much data as possible, but to mix and match a few key metrics relevant to your business that will offer a macro-level view of exactly where your operation is declining and thriving.
So get creative with metrics, and start working smarter, not harder.