Thought Merchants

People. Process. Product.

A simpler Net Promoter Score

Why normality yields better data than ambiguity in NPS tests.

opinion, research,

simpler Net Promoter Score, yes or no.

If you’ve worked on any product in the past 10 years, you’ve undoubtedly come across the Net Promoter Score (NPS).

On a scale from 1-10, "How likely is it that you would recommend our company/product/service to a friend or colleague?”

You sit back. You think, then you say “I’d definitely 6 your product to my friend or colleague”. Now, if you believe there’s something off about that sentence, you’re absolutely correct. No one in their right mind would respond that way. It does not make any sense.

There’s three main flaws surrounding the current NPS metric. We’ll discuss their drawbacks and why Thought Merchants uses simple “yes or no” questions to accurately conclude what NPS can’t.

NPS is a customer loyalty metric. Or a management tool companies use to track, measure, and determine how successful a product is over time, as well as how effective you are at delivering customer value. They group users into three archetypes:

  • Promoters, or those who score 9 and 10, are considered brand advocates, meaning they’ll buy more and spread the word to friends.

  • Passives, or those who score 7 and 8, are in the middle of the spectrum. They neither spread the word or buy consistently, and are easily swayed by competitors.

  • Detractors, or those who score 6 and below, aren’t fans and weigh your brand or product down.

Collectively, these archetypes generate a “NPS Score” between -100 and 100. The basic theory is derived from a correlation between NPS and organic growth to predict the future performance of a company. The higher the NPS score, the more likely you are to outperform your competitors.

NPS became popular when the “as a service” revolution hit. In order to compete, companies turned more customer-focused to meet the needs of buyers. Massive brands like Apple, Amazon, Siemens, American Express, and more, all use this metric to make “data-driven” decisions. With this data, they’re better fit to predict consumer behavior, measure loyalty sentiment, and develop evolve current business strategies.

The first problem with NPS lies in dilution and interruption. Because of it’s rapid popularity, managers of every size business churn out these surveys by any means necessary. Often NPS is asked alongside other hastily thought out questions, yielding less valuable results. From a design perspective, the surveys are messy. They ask a very sensitive product experience question in the middle of the experience, interrupting the user flow.

How can we expect a proper response when we interrupt the experience with a modal question? As well as dropped an array of ambiguous and thoughtless answer possibilities in front of them. NPS offers 11 answer choices for a simple “yes or no” question. According to the highly regarded Hick’s Law, this engrossing amount of choices inhibits our decision making process. From a human approach, we don’t describe our feelings and emotions through such arbitrary means.

Expecting accuracy through ambiguity is impossible. Most of the time, individual numbers on the 10-to-0 answer scale are not clearly labeled. When a user selects “7”, what do they truly mean? This could be positive, neutral, or even negative when the scale is not accurately defined. How often in your daily life do you use a number to gauge your feelings? Rarely, if ever I hope.

This leaves the scale prone to sensitivity and information loss. We can’t argue against 10 being greater than 9. NPS boils these down as equals, losing valuable information in the process. Responses 7 or 8 become null and void, reducing sample size and increasing the chances of statistical error. And 6-to-1 ratings all equal 0. Leaving marketers with various questions for such a simple question, would you recommend this product to your friend, or not?

Consumers are not looking for perfection, they’re looking for a business they can trust. NPS leaves too many questions to be answered when making an accurate, “data-driven” consumer strategy.

This why the human approach is important when researching this type of consumer behavior. Using simple, real-life conversations is more approachable for consumers and gives you the answers you need. When you take away the arbitrary distractions, you can easily separate the two groups of people you are trying to find. And better yet, we don’t have to waste anyone’s time and money trying to arrive at these conclusions.

In the spirit of simplicity, Thought Merchants only runs NPS using yes and no as the answers to yield the one insight your company actually needs in this space.

Would you recommend this product to your friend? Yes… or no.