Quantitative data: all about the specific and objective measures of numerical facts. In other words, things you can measure, like how many commuters take the train to work every week. With quantitative data, we can see numbers visualized as charts or graphs.
Qualitative data: describes subjective or explanatory measures of qualities and characteristics or things that can't be measured with numerical data, like your hair color. Qualitative data is great for helping us answer why questions. For example, why people might like a certain celebrity or snack food more than others.
Qualitative data can then give us a more high-level understanding of why the numbers are the way they are. This is important because it helps us add context to a problem.
eg. a local ice cream shop has started using their online reviews to engage with their customers and build their brand. The owner notices that their rating has been going down.
Quantitative data: How many negative reviews are there? What's the average rating? How many of these reviews use the same keywords? Numerical results that help confirm their customers aren't satisfying.
Why are customers unsatisfied? How can we improve their experience? These are questions that lead to qualitative data.
Quantitative data: the ice cream shop owner sees a pattern, 17 of the negative reviews use the word "frustrated.”