: Different metrics values for the same dimension value in different dashboards So I work for a Media company and we use Google Analytics for tracking our journalists and contributors performance

@Gail5422790

Be careful to compare the same data.

In your segment you are asking GA to show you all sessions that include that Author. This will include all the page views in these sessions, i.e. if someone visits more than that one page during their session, this will also be shown as a hit. The 75K value is for these total page views.

Your other report on the dashboard shows just the page views on the specific pages with the specified Author. For these, the value, accurately, is 27K.

Vote Up Vote Down

@Deb1703797

I'm going to be completely honest right off the bat, I've combed this question over several times and it's quite perplexing, so kudos to you for the challenge. Now, assuming you've double-checked your work and don't have any conflicting filters, errors in your segments, etc., here's what I have to offer. About a year ago, I had an issue similar to this where I was getting double the amount of data when I checked Google Analytics within 48 hours of the day in question, as opposed to after 48 hours (that's a just a rough estimate but two days seemed about the norm). It sort of made sense when taking the reporting lag into account but I still found it odd that I was getting half the data after the fact, so I decided to alter both of the existing custom dimensions by attaching them to two separate events. To ensure it wouldn't affect my bounce rate, I made them non-interaction events. This worked for me, I was getting the correct information at any given point when filtering by the event category and event action. This has led me to believe that custom metrics and dimensions have a tendency to overlap, if you will, and create mismatched data initially. This could be due to the asynchronous nature of the tracking script or perhaps it's another factor. And perhaps there's a filtering mechanism on the platform side that's able to sort this out, or maybe it was just an anomaly. There's no real way for me to know for certain.

In conclusion, I realize that this is largely an anecdotal answer but my suggestion would be to give this a shot. I'm obviously not familiar with how your tracking script is currently set up but adding a unique event to each dimension will help give you an extra layer of durability, through which you can filter each author and event.

Vote Up Vote Down