The long tail refers to the data points at the trailing end of a power-law distribution. A long-tail strategy involves efficiently exploiting these low-impact data points for an aggregated benefit.
Confounding variables can affect the validity of data collected during research studies. It's important for researchers to know what they are and how to identify them.
The Net Promoter Score (NPS) can be gamed, and its definition loses information and precision by treating fairly dissimilar responses in the same way. It should be used together with other UX metrics rather than in isolation.
Product instrumentation tells us when and how much people use different aspects of our product. This insight can inform feature prioritization, validate our assumptions, and identify potential user problems.
A small share of all items produce most of the impact: a few features, a few usability problems, a few customers, and your key persona. Focusing design efforts on those high-impact areas leads to higher success rather than broadly (and thinly) distributed UX work.
Data about what users do is valuable, but not nearly as valuable as information about why people did something. Such "why" insight should drive UX design decisions.
Both UX research techniques help you gain quantitative insight into user behavior. Each method provides different types of information and can answer different kinds of research questions, however.
It's frustrating for users to go back-and-forth and back-and-forth to the same web page, bouncing around without getting what they need. Analytics data can help identify pages that don't help users progress.
Improve design decisions by looking at the problem from multiple points of view: combine multiple types of data or data from several UX research methods.
It can be hard to calculate the return on investment (ROI) for user experience design improvements. But don't get bogged down in less-important details: often simple metrics can give a good-enough estimate to justify UX investments.
Spreadsheet defaults don't generate the most meaningful visualizations of UX data. Modify charts to enhance Context, Clutter (less of it than spreadsheet software likes!), and Contrast.
To gain a holistic picture of your users, exchange data with the non-UX teams in your company who are collecting other forms of customer data, besides the user research you do yourself. You gain; they gain.
Personas are usually a qualitative element in the UX design process, but statistical data from more users can be added for more precision, as long as the personas are still grounded in qualitative insights.
After collecting KPI numbers for two versions of a design, the difference between the two metrics is not statistically significant. Now which version should you launch?
Net Promoter Score (NPS) is a simple satisfaction metric that's collected in a single question. While easy to understand, it's insufficiently nuanced to help with detailed UX design decisions.
