I’ve been thinking lately about why we measure things like, for example, Net Promoter Score (NPS).
What are we actually doing?
These thoughts are prompted by Reid Hoffman’s great new book, Masters of Scale. (In addition to writing books and hosting a podcast, Hoffman is the co-founder of LinkedIn and serves on the boards of Microsoft and PayPal, among others.)
There is something for everyone in this book. For me, what stood out most was Hoffman’s exploration of “first-principles thinking,” a strategy that entails breaking down complicated problems into fundamental basic truths, and moving forward from there to spur innovative solutions.
Adherents include illustrious thinkers such as Aristotle, Johannes Gutenberg, and Rene Descartes. But we don’t need to look to the past for an example: Elon Musk is a prime exemplifier of this kind of thinking.
When Musk looked at building a rocket to send to Mars, he was dismayed at the $65 million price tag manufacturers quoted. So he broke the problem down to create a more effective solution.
He determined that the actual physical components of the rocket made up just 2% of the total cost, then he set about creating his own company to purchase the raw materials at a discount and build it himself.
The result? SpaceX was born. And Musk cut the cost in half and still made a profit.
Now let’s go back to my original question and apply this to customer experience.
Why do we measure NPS?
It’s not to create a score – even though that’s what lots of programs do. It’s about understanding future behavior.
We want something that’s going to tell us whether we are getting better or worse, so we can make any necessary changes. We want to know whether we have customers who are likely to spend more with us, or – horrors! – spend less. That’s the definition of loyalty: customers who buy more products, try our new products, and stay with us longer.
So we believe that this score predicts this behavior. And it often does.
Sure, we can argue about whether NPS is the best measurement, but why bother? That’s not the discussion we should be having.
Going back to first principles, we can determine that likelihood to recommend is an outcome, not a cause.
We are making the assumption that the outcome of being likely to recommend correlates to the likelihood of increased future purchases, which means better loyalty.
But there are two limitations to this approach.
One is that the two outcomes have to be correlated. (And again, it does often work that way.) Some organizations might even create an index using three, four, or five different scores that together get the job done. And that works from a scientific perspective.
But the other challenge of using an outcome is that it doesn’t give us guidance on how to improve.
If all I want to do is make you more likely to recommend me, then I can give you email templates, I can introduce you to others, and I can do other things that help you recommend me.
But those things don’t help you become more loyal.
If we want to understand what will help you become more loyal, we need to apply first-principles thinking and break the challenge down to its fundamental components. That means asking why customers become more loyal.
The easy answer is because they want to. But why will they want to?
We know from Daniel Kahneman and others that it’s typically because they have an emotional reason to. We all make decisions based on emotions first, then rationalize them afterwards. It’s just the way human beings are wired.
In my recent article in Quirk’s magazine, I wrote about the importance of having a motivational emotional North Star, even though the precise emotion is going to differ from brand to brand.
Two of our clients, UKG and Dow, have both spoken publicly about their efforts to measure emotions and the ways they have found that those emotions predict loyalty.
In the case of UKG, confidence is their number one emotion. Dow measures enjoyability, and also confidence.
Here’s why confidence works for both brands: If you’re confident that UKG can handle your payroll well, you’ll probably trust them with taxes and reporting. If you have confidence in Dow’s ability to get you the right products at the right time and right price, you’ll probably be more willing to try their newer products.
Nancy Flowers of Hagerty joined us for a webinar back in April, and discussed how they found that happiness is their emotional North Star. The reason this is important is that when you get the right emotion, it will predict what’s there.
That means that if you are happy working with Hagerty, you’re more likely to buy more from the company in the future. If you’re not happy, you’re less likely to stay with them.
So not only do emotional North Stars help us predict loyalty just as well as NPS – and sometimes, even better – it points you toward impactful ways to improve the customer experience.
That’s why it’s critical include measuring emotions in your CX toolbox. It’s not about creating a score or reporting. (Though you’ll likely do both those things.)
It’s about taking action.
Getting at the fundamental piece of the challenge you face – an understanding of what builds loyalty in your customers – empowers you to design effective, innovative solutions against that knowledge.
It might not take you all the way to Mars, but it can certainly help your impact on the business soar.