Quantitative Data

Quantitative data is numeric, countable information about user behavior — visit counts, conversion rates, session duration — answering “how many” and “how much”.

Quantitative data's strength is scale and objectivity: you can rely on millions of visits, take trends and make statistical decisions; unlike qualitative data, one person's sharp comment does not move the number. But quantitative data has a serious limit that is repeatedly forgotten: it says what happened, not why. A 68% exit rate is a fact, but it does not itself say whether the cause is bad design, high price or simply the wrong audience. It has two more traps: a number without a statistical basis (a percentage on a small sample is unstable); and the illusion of precision — a figure like 68.3% looks exact, but if the metric definition or data-collection quality is fuzzy, that decimal means nothing. Quantitative data is excellent for proof and monitoring and needs qualitative data to understand cause.