How you design a survey can change the answers you get. Question wording, question order, response labels, the number of response options, and whether you include a midpoint can all influence how respondents answer.
Outliers are unusually high or low observations that sit far from the rest of a dataset. In A/B testing, a small number of extreme values can materially change averages, variance, confidence intervals, and the conclusion you draw from a test.
This matters particularly for revenue metrics such as average order value and revenue per visitor, where a handful of unusually large purchases can have a disproportionate effect.
An outlier is not automatically bad data. It might be a recording error, unusual customer behavior, or a genuinely valuable segment. The important part is identifying it, understanding why it occurred, and deciding how it should be handled before it distorts your analysis.
Your users will make mistakes. It’s inevitable. That’s what error messages are for—but so many companies fail to follow best practices, and they’re pissing off potential customers in the process.
So, how can we better design error messages to improve the user experience and increase conversions?
User experience is a nebulous term. What defines a “good” UX from a “bad” UX, and what do the gradations look like between the two poles?
Fear and greed are two of the three great forces in the world, according to Einstein (the third is stupidity).
They’re also two triggers that not only stock markets (in the form of the Fear & Greed index), but also marketers and copywriters have been well aware of for years.
That’s because they are powerful emotions that, when used properly, drive people to take action.
A large part of landing page optimization is focusing your visitors’ attention on what matters.
There are many design theories on how exactly to do that. Most will include using what is known as a visual cue to direct attention towards a desired object.
There’s a philosophical statistics debate in the A/B testing world: Bayesian vs. Frequentist.
This is not a new debate. Thomas Bayes wrote “An Essay towards solving a Problem in the Doctrine of Chances” in 1763, and it’s been an academic argument ever since.
Perception isn’t always the same thing as reality, even when it comes to something as “objective” as your product’s value.
In fact, the perceived value of your product is fairly malleable. There are countless studies, as well as anecdotes, that support the notion that you can tweak small things to increase your product’s value perception.
A hero image is the large, prominent visual that appears at the top of a webpage, usually alongside the headline, value proposition, and primary call to action. A good hero image helps visitors understand what you offer, who it’s for, and why it matters. It can show the product, demonstrate an outcome, provide context, or build credibility.
A good user experience equals more money. But how do we measure user experience? How do we know if it’s getting better or worse?