Net Promoter Score Experiment

We're building a comprehensive knowledge library about product development as part of our mission. The library is for anyone looking to make better decisions — primarily decisions about product development. Whether you're an inventor, a product manager, or a Chief Product Officer, using the right research methods and experiments increases your chances of building the right things for the right audience. Today we'll introduce the Net Promoter Score (NPS) validation method.

When to Use This Experiment?

NPS is worth deploying once a product or audience already exists and you need to measure customer loyalty regularly and catch any decline in customer experience early.

• An active customer base exists that can answer based on real experience with the product.

• A single, comparable loyalty metric is needed — one you can track over time and across segments.

• The customer experience has natural trigger points (after purchase, after a support contact, after completing a key action).

• The team is ready to act on feedback, not just collect it.

• A signal about a stated attitude is enough; the method does not measure actual behavior and therefore offers no hard proof of validation.

Basic Experiment Principles

The principle is simple: customers are asked, on a scale of 0 to 10, how likely they are to recommend the product. Based on their answers they are split into promoters (9–10), passives (7–8), and detractors (0–6), and the score is calculated as the percentage of promoters minus the percentage of detractors. A follow-up question about the reason for the rating reveals what lies behind the number — and the survey must be kept short so that as many promoters and detractors as possible respond.

1. Pick the moment of measurement. Choose a trigger tied to a specific experience milestone — typically shortly after purchase, after a support interaction, or after completing a key action, while the experience is still fresh.

2. Ask the key question. Ask "How likely is it that you would recommend our product to a friend or colleague?" on a scale of 0 to 10. Keep the survey short so that as many promoters and detractors as possible respond.

3. Add an open-ended question. Right after the rating, ask for the reason behind the score. The number alone won't reveal why a customer answered the way they did.

4. Collect and evaluate the data. Split respondents into promoters (9–10), passives (7–8), and detractors (0–6). The score is calculated as NPS = % promoters − % detractors and ranges from −100 to 100. A value above +40 is generally seen as very good, but the threshold varies by industry and there is no fixed rule. It's worth tracking the absolute score as well as the trend and the share of detractors — a sudden drop or a recurring theme in the open-ended answers is a signal to act.

5. Close the feedback loop. Actively reach out to detractors in particular, sort their complaints into actionable segments, and respond to them. This step turns dissatisfied customers into promoters and shows that feedback has an impact.

6. Identify the risks. NPS measures a stated opinion, not actual behavior, so false positives are a risk. The number alone hides the "why" and, without the open-ended question, leads to mistaken conclusions. The result is sensitive to timing, sample size, and cultural differences in how people use the scale. Because the comparable threshold differs by industry, the absolute value is misleading on its own and is no hard proof of validation.

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Real-World Experiment Example

Link to research: How a jewelry e-shop doubled revenue with NPS

London jeweler Taylor & Hart, which specializes in bespoke engagement rings made from ethically sourced diamonds, chose NPS as the "one metric that matters" and tracked it daily. It soon became clear that many customers were reluctant to buy a ring from a purely online seller without seeing it in person. So the company built its entire approach around caring for the customer experience.

They split measurement into two milestones. About an hour after the order, a "service NPS" goes out to rate the consultant's work in helping choose the ring, while a "standalone product NPS" is sent 40 days after purchase, once the ring has been made, shipped, and delivered. Analyzing both scores revealed that the product NPS was consistently 10 to 15 points lower than the service NPS for the ring selection — a sign that the problem lay in the product, not the service. That led to a redesign of the entire manufacturing and logistics process.

The results were visible on wall-mounted screens in the office, and the team addressed every piece of negative feedback. The score now holds steadily above 80 for both service and product, and the disciplined use of data translated into roughly 70% revenue growth and a doubling of annual turnover within a few years.

What Can Be Tested With This Experiment?

NPS is strongest at measuring loyalty and willingness to recommend; it pinpoints exactly where in the customer experience satisfaction breaks down and which problems erode customer trust the most.

• Loyalty validation: customers' willingness to recommend the product; the signal is a score above the industry benchmark (generally above +40).

• Identifying friction points in the customer journey: comparing NPS at different milestones (e.g. service versus product) shows which phase drags satisfaction down.

• Surfacing detractors' specific pain points: the open-ended follow-up question brings recurring reasons for low ratings to the surface.

• Exposing a bad product decision: regular measurement catches a sudden drop after a new release or a process change.

• Comparing loyalty across segments: comparing scores by customer type, channel, or region reveals where loyalty is strongest and where it's weakest.

• Prioritizing improvements: linking NPS to churn or repeat-purchase rates shows which changes actually move the business result.