UX and Net Promoter Benchmarks of Grocery Websites

Online grocery shopping has increased substantially over the past few years due to the COVID-19 pandemic. In 2019, online grocery sales grew steadily, but they accounted for only a modest portion of sales. Now, online grocery sales are booming, with estimated annual sales of 97.7 billion in 2021, an impressive 57% increase for the market

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What Is the Product-Market Fit (PMF) Item?

A social media platform, a GPS heads-up display, a video streaming platform: all are examples of viable products … that failed. The failure came despite often substantial financial funding and putatively useful features. Their failures were blamed on poor product-market fit. Predicting a prospective product’s success in the market isn’t easy. But there’s a strong

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UX and Net Promoter Benchmarks of Seller Marketplace Websites

When we think of how the internet has changed commerce, we often consider our ability to browse and purchase products from around the world easily from the comfort of our homes with our mobile phones. But the internet has also enabled millions of people to easily sell their products to global consumers. That selling often

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Completion Times and Preference for Sliders vs. Numeric Scales

In earlier articles, we investigated the effects of manipulating item formats on rating behaviors—specifically, we compared sliders to traditional five-point and eleven-point radio button numeric scales. For those analyses, we collected data from 212 respondents (U.S. panel agency, late January 2021) who used radio buttons and sliders to rate online shopping websites (e.g., Amazon) and

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Why Do People Hate the Net Promoter Score?

The Net Promoter Score is ubiquitous, with many large organizations using it as a key metric. But despite its widespread adoption, there are vocal critics. It’s been called snake oil, deceptive, fake science, and harmful. In our webinar series and on our website, we’ve addressed several aspects of the NPS, including the enmity toward it.

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How to Statistically Analyze Net Promoter Scores

In a famous Harvard Business Review article published in 2003, Fred Reichheld introduced the Net Promoter Score (NPS). The NPS uses a single likelihood-to-recommend (LTR) question (“How likely is it that you would recommend our company to a friend or colleague?”) with 11 scale steps from 0 (Not at all likely) to 10 (Extremely likely).

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Sample Sizes Needed to Exceed NPS Benchmarks

So, you’re planning to collect data and you want to know whether your Net Promoter Score (NPS) is significantly above 50%. Established benchmarks can help research teams know if they’ve reached acceptable thresholds, such as a high Net Promoter Score (e.g., more than 50%). A high NPS is associated with successful product launches. But an NPS

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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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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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