Statistical significance isn't a metric we provide in our platform, but it can be calculated fairly easily using a statistical significance calculator (many of which are readily available through an online search).

Statistical significance refers to the likelihood that a difference between two data points reflects reality. When using a larger sample size, you'll be more likely to see statistically significant data.

When considering the statistical significance of data in our platform, it's important keep in mind the following:

For an audience of 1,000, a change in % between two waves is much more likely to be robust and significant than for an audience of 100.
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Typically, statistics software will flag a value difference with 95% confidence, meaning it's 95% certain that the difference displayed will fall within the margin of error (which is typically, but not universally, set at +/- 3%.). For example: In a single choice question, 80% of respondents have selected option A and 20% option B. The statistical software used has flagged the interval of 60% between the two options as significant. This means that there is a 95% chance that the difference between Answer Option A and B is within the range of 57% and 63%.

When breaking our data sets down into smaller audiences - thereby lowering the available sample size - some of the smaller percentage changes may not be statistically significant. This doesn't mean that the data can't be trusted or that there is nothing to be learned from it, but rather that there's a higher chance that the differences between data points sit outside of the margin of error. When working with data that isn't statistically significant, it's advisable to work with a degree of caution and also consider the wider context of the results.