When making sense of wave-on-wave changes, always consider the following:
Could seasonal variation be having an impact?
If there’s a shift in shopping patterns between two waves, it could be influenced by one wave being just before Christmas and the other just after.
Are there local market factors at play?
We see some of the biggest jumps in data when a country’s government intervenes to allow/prohibit a particular behavior or service. For example, when a social media service gets restricted in a particular country, there’s often a noticeable impact on global usage - particularly if that country has a large population.
Have there been any changes to the question, or any other aspect of the survey set-up?
Changes in question format or wording can have an impact on responses. Such changes will be noted in the question details on our platform.
Is the change meaningful?
While it’s tempting to see changes of 1-2 percentage points as meaningful, they could fall within the margin of error (making them statistically insignificant).
For example, if a country had an online population of 3,000,000 and a sample size of 1,500, the margin of error would be 2.5%. Therefore, a wave-on-wave change smaller than this would be statistically insignificant. However, in other markets, smaller changes could be significant; the US has an online population of c. 200m and a quarterly sample size of 25,000 in GWI Core, meaning the margin of error is just 0.6%.
In short, you should consider both the universe size and the sample size when interpreting wave-on-wave changes. Although you can find statistical significance calculators online to make precise calculations, avoiding reading too much into changes of 1-2 percentage points when working with smaller sample sizes is a good starting point and sufficient for most analyses.