Research focused on numerical measurement with the goal of generalizing findings from a sample to a broader population. Answers 'how much,' 'how many,' and 'how often.'
Definition: Research focused on numerical measurement with the goal of generalizing findings from a sample to a broader population. Answers 'how much,' 'how many,' and 'how often.'
Quantitative Research numerically measures a phenomenon and, with a sufficiently large sample, generalizes those findings to a broader population. It answers questions of "how much," "how many," and "how often"—dealing in numbers, metrics, and statistical analysis.
Use quantitative research when you need to:
The key distinction is generalization. Quantitative research aims to say something about a population (your entire user base, the market) based on a sample. This requires sufficient sample size and appropriate sampling methods.
Running a survey with 15 convenience-sampled respondents produces numbers, but it is not quantitative research in the rigorous sense—you cannot generalize from it. The numbers become qualitative indicators rather than population estimates.
Quantitative data excels at showing what is happening at scale ("70% of users drop off on the pricing page") but cannot explain why. Qualitative research provides the explanatory depth ("Users don't trust the site because they don't see familiar payment logos").
The combination—mixed methods—builds the most complete picture. Quantitative findings without qualitative context are incomplete; qualitative insights without quantitative validation may not generalize.
Research focused on understanding the 'what' and 'why' through rich stories, observations, and context. Seeks depth of understanding rather than statistical measurement.
A research approach that deliberately combines qualitative and quantitative methods to build a more complete picture. Qualitative explains the 'why'; quantitative measures the 'how much.'
The practice of combining multiple data sources, methods, or perspectives to build more robust research findings. Reduces reliance on any single source and increases confidence in conclusions.
A Core Method of asking at scale using standardized questions. Enables data collection from larger samples but sacrifices the depth of interviews for breadth and standardization.
This term is referenced in the following articles:
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