Weighting and balancing is a survey feature that allows you to eliminate sample bias in your online surveys. You can adjust the captured data to represent the population accurately. This question helps researchers eliminate bias that occurs when the data derived from the survey does not represent the target population accurately to make sound decisions.
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.
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:
The advantages of weighting and balancing are:
Learn how to set up and use this feature with our help file on weighting and balancing.