Quantitative methods translate user experience into measurable data. A survey is a structured questionnaire distributed to many users to collect both quantitative and qualitative data about attitudes, preferences, and demographics. Survey questions come in two flavours: closed-ended questions offer predefined answer options such as multiple choice or rating scales and produce quantitative data, while open-ended questions invite free-text responses and yield qualitative insights. Among rating scales, the Likert scale typically offers 1–5 or 1–7 points measuring agreement or satisfaction, ranging from "Strongly disagree" to "Strongly agree".
Two widely used standardised questionnaires help benchmark and compare experiences. The Net Promoter Score is a loyalty metric based on the question "How likely are you to recommend us?", scored from 0 to 10, with the score calculated as the percentage of Promoters (those answering 9 or 10) minus the percentage of Detractors (those answering 0 to 6). The System Usability Scale, or SUS, is a 10-question questionnaire that produces a score from 0 to 100 measuring perceived usability, with a score above 68 considered above average. These instruments allow teams to track changes over time and compare against industry norms.
Behavioural analytics complement survey data by capturing what users actually do. Tools like Google Analytics, Hotjar, and Mixpanel provide quantitative data on page views, click paths, drop-offs, and conversion rates. A heatmap is a visual representation of where users click, move, or scroll on a page, with warmer colours indicating more activity, and tools such as Hotjar and Crazy Egg help teams spot attention patterns. Session recordings replay actual user sessions, including mouse movements, clicks, and scrolls, so researchers can observe confusion and friction in context. Funnel analysis tracks the percentage of users who complete each step in a multi-step process such as a checkout flow, identifying exactly where drop-offs occur.
For more precise attention data, eye tracking uses specialised hardware to measure where users look, for how long, and in what order, revealing visual hierarchy and elements that get overlooked. Research from the Nielsen Norman Group has shown that users tend to scan web content in an F-shaped pattern: reading across the top, then down the left side, with progressively shorter horizontal scans as they move down the page. Recognising this pattern helps designers place key messages, calls to action, and headings where they will be seen.