Quantitative Analysis

Quantitative analysis describes analytical methods based on countable data, which use statistical procedures to deliver statements about distributions, means and relationships. Unlike qualitative analysis, which explores meanings and motives, quantitative analysis answers how much, how often and how strong. It is standard in web analytics, marketing research and product development.

Methods and tools

Typical procedures are descriptive statistics, hypothesis tests, regression analysis, analysis of variance, factor analysis and time series analysis. Tools range from spreadsheets through specialised software like SPSS or R to BI platforms with interactive dashboards. A sufficiently large data base is a prerequisite, since statistical statements require samples of reliable size.

When quantitative analysis fits

Quantitative analysis fits questions whose answer can be measured. How high is the conversion rate. Which campaign achieves the highest ROAS. Which customer journey steps lead most often to churn. For questions about motives, perceptions or unmet needs, qualitative analysis delivers the better answers, often in tandem with quantitative research.

Practical use

In day to day marketing, quantitative analysis underpins almost every data driven decision. A/B tests, campaign evaluations, customer lifetime value calculations, funnel analyses and forecast models are all quantitative methods. Anyone optimising newsletter marketing uses quantitative analysis to evaluate subject line tests, send times and segment strategies.