Google Analytics Impressions – Pros And Cons
There are two methods of determining impressions in Google Analytics. Both methods do not involve actually tracking the number of times your ad is served or clicked on. Instead, impressions are calculated by counting the number of times your ad is shown to a user. There is no direct way to get the number of times your ad is actually served or clicked on. To get the number of times your ad was served or clicked on, you would have to combine your Google AdSense data with your Google Analytics data. The first, and most common, way to measure impressions is called “Standard Reporting,” a less precise but more common method. It uses two metrics: a page view, which counts how many times a page is loaded, and an ad impression, which counts the number of times your ad is shown on the page. The second way to measure impressions is called “Event Tracking,” which is a more precise but less common measurement method. It uses two metrics as well: a page view, which counts how many times a page is loaded, and an ad call, which counts the number of times your ad is served or clicked on.
Impressions are measured on the page level, not on the blog level. Pages have different gauges than blogs. A page can have one or more impressions and it changes every time the page is loaded. An impression is a page view. There are two kinds of page views. They are: “Initial” and “Refreshed”. An initial page view means the first time your page is seen by one visitor. A refreshed page view means the next time your page is seen by the same visitor.
Conclusion
We hope that you enjoyed our blog on how to find impressions in Google Analytics as much as we enjoyed writing it. We know that it can be hard to find the impressions you need in Google Analytics and we hope that we were able to help you with this. Since we want our readers to get the most out of our blog posts, we encourage you to leave a comment and let us know if you have any other questions about impressions in Google Analytics. We will be happy to help if we can. Thank you for reading!