If more and more users use your right to refuse cookies, then this is sometimes strongly reflected in visitor numbers and conversions. What is good for data protection is a problem for many companies. Because without enough data, it’s hard to determine how good a marketing campaign was and/or how successful a project is.
How do I make more users accept the cookies?
There are a number of tools that meet regulatory requirements, depending on which system you use. But what many people forget is that the look and settings have a big impact on whether users end up allowing cookies or not. The trend is to make the consent of all cookies as large and conspicuous as possible, and to offer other options but make them more inconspicuous or harder to access. The reason is simple: fewer users bother to click through the settings and want to consume the information quickly. This makes clicking “Agree” more likely than clicking “Settings” and “Save” again. Of course, the cookies that are not necessary must not be preselected in the submenu.
Here, using Telekom as an example:
What are some ways to improve the data in Google Analytics?
Basically, there is always less data now than before. Based on the large fluctuations, Google has also recognized that something needs to be done here and has therefore released a new version of Google Analytics. Read more in our last blog post: Google Analytics Update.
There is a recent article from Googlethat we would like to refer to here. Here, Google explains how machine learning is used to fill in the missing data.
Caution trap, reportings!
Unfortunately, the problem drags on. Those who make data comparisons with the previous year after the new law in May 2020 (and the hopefully timely changeover) will mostly have a negative trend in visitor data. This is, of course, a result of the fact that all users were tracked in the previous year and now significantly less data is coming in. Some tools measure how many users have rejected the cookies. This gives you an approximate size that you can still use to determine if the trend is still positive or negative despite the loss of data. To what extent the gaps Google Analytics 4 picks up with machine learning has yet to be determined.
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