How often does a customer rage click on this app? How much revenue did our company make last year? How many people attended last week's webinar? Quantitative variables can tell you 'how many,' 'how much,' or 'how often.' If it can be counted or measured, and given a numerical value, it's quantitative in nature. Quantitative data refers to any information that can be quantified - that is, numbers. Qualitative and differ in their approach and the type of data they collect. They both have their advantages and disadvantages and often complement each other. It's hard to conduct a successful data analysis without qualitative and quantitative data. Qualitative research focuses on the qualities of users-the 'why' behind the numbers.

Quantitative research is based on numeric data. Qualitative data is descriptive in nature, expressed in terms of language rather than numerical values.

Quantitative data refers to any information that can be quantified, counted or measured, and given a numerical value. Knowing both approaches can help you in understanding your data better-and ultimately understand your customers better. So let’s demystify the complexities by thoroughly explaining the similarities and differences between qualitative and quantitative data and how they are both crucial to the success of any data research and analysis. But what’s the difference between the two? And when should you use them? And how can you use them together? And you already know it can be incredibly complex.Īt its simplest, data can be broken down into two different categories: quantitative data and qualitative data. If you’re reading this, you likely already know the importance of data analysis.

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