Data insights
Insights,Marketing Research,Marketing strategy

From data points to data insights

As a marketing leader you are usually seeing different types of data, most of the time data points that are somehow related, but it is your job to find those relations, and make data points into data insights. Data insights are the ones that will make a difference in your day-to-day and with your brand’s strategy.

A good practice to go from data points to data insights is to find relationships between the different points or variables. The main idea of relationship analysis is to find associations between the different variables in your data. Sometimes you can think that Variable A and Variable B look like they might have a relationship, but it is always a best practice to run a relationship analysis test to make sure the data does not only look like it is associated, but you have numbers to back it up.

The relationship analysis test measures aspects such as presence if there is an actual relationship between the variables), direction or pattern (if it is positive or negative), and strength of the association (if it is meaningful). These three aspects are important to help you conclude if your data points are related and will help you turn them into insights that you can act on.

They are two types of relationship analysis:


they will help you look for patterns between two nominal or categorical variables (not metric). With the cross tabs to confirm if the relationship is significant, you should run a Chi-square analysis.


this will help you look for a relationship between two metric variables. And to confirm if the relationship is significant you will have to use the correlation coefficient (R).

Finding relationships between different data points is a crucial skill for a marketing leader. You will be given many data points often, but questioning if they are related and if this relationship is significant will help you start looking at insights, that can be the foundation for many marketing strategies.

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