In today's data-driven environment, we're continually striving for actionable insights that enable us to improve our value proposition to our customers.
The Net Promoter Score is a customer loyalty metric that measures the willingness of customers to recommend a company's products or services to others. It is used as a proxy for gauging customers' overall satisfaction with a company's product or service and, by extension, customers' loyalty to the brand. Customers are surveyed on one single question: On a scale of 0 to 10, how likely are you to recommend this company's product or service to a friend or a colleague? Based on their ratings, customers are then classified into three categories: detractors, passives, and promoters. Anyone who scores a 9 or 10 is a promoter. Your NPS is calculated by subtracting the number of detractors from the number of promoters, and then dividing that by the total number of respondents.
With that in mind, there are two fundamental shortcomings of NPS. For starters, NPS is not directly actionable. A low NPS score by itself gives you no actionable vector. Let's say your NPS score is 3. What should you do to fix it? Is it because your customer service reps are doing a poor job? Is your website performing badly or confusing your customers? Is your interactive voice response system a mess? Are you not answering your emails? It's hard to know where to start to fix the problem.
Secondly, NPS is a rear-view mirror. Another serious problem with NPS is that the traffic accident has already happened. In other words, the customer already had the bad experience. What we need is real-time information that alerts to problems that are happening right now and that are affecting customer perceptions of our brand.
There is another customer experience metric in widespread adoption. The Customer Satisfaction Score (CSAT) is derived by asking customers how satisfied they are with their recent interaction—often a purchase or a customer service call. While this is certainly more focused on the experience customers have with the company, it's still measuring an event that's already occurred.
A new, additive approach is needed: operational CX metrics.
I would like to propose a different approach that is additive to both NPS and CSAT, is more actionable, and gives you a pathway to boost both NPS and CSAT. That pathway is through tracking, measuring, and basing your improvement actions on the operational performance of customer journeys as customers experience them. And taking it one step further, then embedding a quality approach throughout the entire IT team that develops and operates the IVR, Web, email, and SMS systems that are the channels of communication and touchpoints with your customers.
These operational CX metrics need to have the following qualitiess:
- A proactive approach that requires new instrumentation;
- Based on real customer journeys on the front lines of your customer service channels;
- Scientific, objective, quantifiable, and repeatable; and
- Analogous to a canary in a coal mine; it's an early warning system.
Here are two real-world examples that show how an operational CX metrics approach found problems that an NPS approach would never find.
Chatting with thin air. A leading global consumer technology company managed to avoid frustrating its customers by quickly identifying a chat issue that would have shaken customer confidence in its customer service. During testing of its chat systems, we found that one in five chat sessions never connected. When the IT team investigated, it was able to isolate the issue to a single server, and further investigation showed that the server was not configured correctly. The server was running (so device monitoring showed all systems were working) but the configuration was incorrect. It was only by mimicking a customer interaction that we were able to identify the issue. This is precisely the type of issue that irritates people immensely.
Who dropped the call? The call center for a healthcare provider had been alerted by customers that its calls were being dropped. Call-center agents knew about it and had reported it. The IT team had investigated it but was stumped. It was through granular call monitoring that we were able to detect a pattern of dropped calls at 3pm every day. When our team exposed the problem, the agents said: "Oh, right, the 3 o'clock problem!" Once IT got this clue, it could isolate the issue to server updates that occurred daily at 3 p.m. Problem solved!
By focusing our efforts on measuring our operational performance, understanding where it needs improvement, and using that information to inform the development of our CX infrastructure, we can develop a process that continually drives to excellence. And, we can identify potential CX meltdowns before they even occur.
Alok Kulkarni is co-founder, chairman, and CEO of Cyara.