Weighting and balancing

Example of weighting and balancing

For example, your business deals with selling men's clothing and accessories, and males make up 80% of your total customer base. If you conduct a survey and gather data from 50% males and 50% females - you're in for significant sample bias. The survey data leans towards females, who account for 50% of the captured data, but only account for 20% of your customer base. I this case, apply weighting and balancing to control or eliminate responses shared by females in the survey.

Uses of weighting and balancing in surveys

The primary motive of weighting and balancing is to yield accurate data-backed decisions. This is achieved by eliminating data that does not add value to representing the population accurately. You can use weighting and balancing to eliminate demographic biases for the following and more:

• Age bias

• Gender bias

• Location bias

• Educational level

• Marital status

• Number of children

Advantages of weighting and balancing in surveys

The advantages of weighting and balancing are:

• Eliminate demographic bias

• Eliminate psychographic bias

• Accurate decision making

How to use weighting and balancing in your surveys?

Learn how to set up and use this feature with our help file on weighting and balancing.