Quantitative UX Research

What it is

Quantitative UX research uses numbers to describe behaviour at the scale interviews cannot reach: how many people start, where they stop, how long a task takes and how often it succeeds. It describes what happened; it does not explain why. The difference from A/B Testing is deliberate — this is measuring, that is intervening.

Why it matters

Five interviews tell you a problem exists; a funnel tells you whether it costs 2% or 40% of your users, which decides whether it is next week’s work or next year’s. Without numbers, prioritisation is decided by whoever tells the most vivid story, and the most vivid story is usually the most recent one rather than the most common. The numbers also survive the departure of the person who ran the interviews.

In this track

1. What to measure (03-design-ux/24-quantitative-ux-research/01-what-to-measure) — funnels, drop-off, task success and time on task, and which of them answers your question.
2. Instrumenting and reading the numbers (03-design-ux/24-quantitative-ux-research/02-instrumenting-and-reading-the-numbers) — getting the events defined before you need them, then reading them without fooling yourself.

Prerequisites

• User Research (03-design-ux/05-user-research)

Go deeper

• A/B Testing (03-design-ux/39-ab-testing) — the next step, where you change something instead of only watching.
• Google Analytics 4 (GA4) (03-design-ux/06-google-analytics-4-ga4) — the tool most teams collect these numbers with.
• Usability Testing (03-design-ux/33-usability-testing) — the qualitative partner to every number here: it explains the drop-off the funnel shows.
• From findings to decisions (03-design-ux/05-user-research/04-from-findings-to-decisions) — ranking a measured problem against everything else.