Blog

Topics

UX and Net Promoter Benchmarks of Mass Merchant Websites

With the COVID-19 pandemic’s effect on consumer shopping behavior (e.g., increased online shopping for delivery or contactless pickup), mass merchant revenues rose dramatically in 2020 and the first part of 2021. For example, Target reported a $15B sales growth in 2020, higher than its total sales growth over the past 11 years. For another example,

Read More »

Campbell’s Law and the Net Promoter Score

To make better decisions, you need data. That’s become a truism. But can the process of using the data lead to bad outcomes? It seems like a hypothetical question, but it doesn’t take long to find a few key metrics that, when tracked, can lead to unwanted outcomes: On-time departures: On-time flight departures for airlines

Read More »

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

Read More »

How to Write a Survey Question

A blank page can lead to writer’s block. Writing survey questions can also seem like trying to write the Great American Novel. It can be particularly daunting knowing that subtle word changes may lead to unanticipated responses. The good news is that you don’t have to start from scratch each time. Instead, you can follow

Read More »

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

Read More »

The UMUX-Lite Usefulness Item: Assessing a “Useful” Alternate

When Kraig Finstad (2010) developed the Usability Metric for User Experience (UMUX), his goal was to replace the ten-item System Usability Scale (SUS, a popular measure of perceived usability) with a shorter questionnaire that would (1) correlate highly with the SUS and (2) have item content related to the ISO 9241 Part 11 international standard,

Read More »

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,

Read More »

From Statistical to Practical Significance

Hypothesis testing is one of the most common frameworks for making decisions with data in both scientific and industrial contexts. But this statistical framework, formally called Null Hypothesis Statistics Testing (NHST), can be confusing (and controversial). In an earlier article, we showed how to use the core framework of statistical hypothesis testing: you start with

Read More »

The Anatomy of a Survey Question

We’ve written extensively about question types, the elements of good and bad writing, why people forget, and common problems with survey questions. But how do you get started writing questions? Few professionals we know have taken a formal course in survey development and instead rely on their experiences or best practices. Despite being called questions,

Read More »

“Does What I Need It to Do”: Assessing an Alternate Usefulness Item

The UMUX-Lite is a two-item standardized questionnaire that, since its publication in 2013, has been adopted more and more by researchers who need a concise UX metric. Figure 1 shows the standard version with its Perceived Ease-of-Use (“{Product} is easy to use”) and Perceived Usefulness (“{Product}’s capabilities meet my requirements”) items.   Figure 1: Standard

Read More »

A Decision Tree for Picking the Right Type of Survey Question

Crafting survey questions involves thinking first about the content and then about the format (form follows function). Earlier, we categorized survey questions into four content types (attribute, behavior, ability, or sentiment) and four format classes (open-ended, closed-ended static, closed-ended dynamic, or task-based). As with any taxonomy, there are several ways to categorize response options (e.g.,

Read More »

Statistical Hypothesis Testing: What Can Go Wrong?

Making decisions with data inevitably means working with statistics and one of its most common frameworks: Null Hypothesis Significance Testing (NHST). Hypothesis testing can be confusing (and controversial), so in an earlier article we introduced the core framework of statistical hypothesis testing in four steps: Define the null hypothesis (H0). This is the hypothesis that

Read More »
0
    0
    Your Cart
    Your cart is emptyReturn to Shop
    Scroll to Top