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Categorical Variable

A categorical variable (also called “attribute variable”) is a qualitative variable where each row is assigned one out of a limited number of possible values. The potential values are often fixed and lack an intrinsic order. 

For example, when flipping a coin, the values represented in a categorical variable would be heads or tails. Item characteristics, like color or size, can also be represented in a categorical variable since they’re unique and since there is no objective way of adding higher or lower numerical values to each due to their qualitative nature.

Examples of categorical variables in sales and marketing

In sales and marketing, categorical variables, like demographic information and other customer data, can help to segment your data according to different user personas, to better determine which ads or products they should be targeted with. A categorical variable can be different characteristics of your products or services, responses to a social media poll, or information about your audience.

You can also find categorical variables in the payment methods you accept, your working hours, or the results of a competitive analysis.

How are categorical variables used?

Although qualitative values can’t be sorted or measured, they’re still extremely valuable when studying the competition or developing a customer persona.

When developing a customer persona, the profile will be filled with categorical variables, like demographics, which are valuable to determine whether or not your marketing efforts are going to the correct users. Often, the more narrow and precise these categorical variables get, the better you’ll be able to target your audience.

Categorical data can also be used to contextualize your quantitative data, like adding descriptions and context to understand the success or failure of a marketing effort, and determine how to recreate effective campaigns.

Common categorical variable issues

Often, categorical data will require larger data samples to evaluate, which can be more expensive and time-consuming to put together. Since no objective scale can be used to measure categorical variables, it isn’t always obvious which categorical variables are relevant to a specific scope.

Categorical variables cannot be used alone to determine the success of your efforts, and will often require quantitative data to provide a full picture. 

Learn more about categorical variable

What is data exploration:
https://www.polymersearch.com/blog/sales-intelligence
 

The Best 10 AI Tools to Analyze Data:
https://www.polymersearch.com/blog/the-best-10-ai-tools-to-analyze-data