How to Compare a Net Promoter Score with a Benchmark

We recently described how to compare two Net Promoter Scores (NPS) statistically using a new method based on adjusted-Wald proportions. In addition to comparing two NPS, researchers sometimes need to compare one NPS with a benchmark. For example, suppose you have data that the average NPS in your industry is 17.5%, and you want to

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Sample Sizes for Comparing Net Promoter Scores

Sample size estimation is a critical step in research planning, including when you’re trying to detect differences in measures like Net Promoter Scores. Too small of a sample and you risk not being able to differentiate real differences from sampling error. Too large of a sample and you risk wasting resources—researchers’ and respondents’ time and,

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UX and Net Promoter Benchmarks of Food Delivery Services

The food delivery market has been growing significantly over the past five years. That growth exploded in the United States from $17 billion in 2018 to $26 billion in 2020 (partly due to COVID-19). This market is highly competitive and has ultra-thin profit margins. Technologies such as route optimization enable faster and cheaper delivery, but

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Sample Size Estimation for NPS Confidence Intervals

Sample size estimation is a critical step in research planning. It can also seem like a mysterious and at times controversial process. But sample size estimation, when done correctly, is based mostly on math, not magic. The challenge is that the math can get complex, so it becomes easier to defer to simple rules or

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Evaluating NPS Significance Tests with Real-World Data

The Net Promoter Score (NPS) is widely used by organizations. It’s often used to make high-stakes decisions on whether a brand, product, or service has improved or declined. Net Promoter Scores are often tracked on dashboards, and any changes (for better or worse) can have significant consequences: adding or removing features, redirecting budgets, even impacting

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How to Statistically Compare Two Net Promoter Scores

When we wrote Quantifying the User Experience, we put confidence intervals before tests of statistical significance. We generally find fluency with confidence intervals to be easier to achieve and of more value than with formal hypothesis testing. We also teach confidence intervals in our workshops on statistical methods. Most people, even non-researchers, have been exposed

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UX and Net Promoter Benchmarks of Auto Insurance Websites

Fifteen minutes could save you 15%. Nationwide is on your side. You’re in good hands with Allstate. Auto insurance commercials are ubiquitous. It’s no wonder, considering the market. In 2020, the population of the United States was 331,000,000, and 230,000,000 Americans were licensed drivers. If you drive, you should have auto insurance. Until recently, most

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Evaluating NPS Confidence Intervals with Real-World Data

The Net Promoter Score (NPS) is a popular business metric used to track customer loyalty. It uses a single likelihood-to-recommend (LTR) question (“How likely is it that you will recommend our company to a friend or colleague?”) with 11 scale steps from 0 (Not at all likely) to 10 (Extremely likely). In NPS terminology, respondents

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Feature Open Ended Questions 011320

Five Reasons to Use Open-Ended Questions

Despite the ease with which you can create surveys using software like our MUIQ platform, selecting specific questions and response options can be a bit more involved. Most surveys contain a mix of closed-ended (often rating scales) and open-ended questions. We’ve previously discussed 15 types of common rating scales and have published numerous articles in

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Confidence Intervals for Net Promoter Scores

The Net Promoter Score (NPS) is a widely used metric, but it can be tricky to work with statistically. One of the first statistical steps we recommend that researchers take is to add confidence intervals around their metrics. Confidence intervals provide a good visualization of how precise estimates from samples are. They are particularly helpful

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