I'm using segments to check the number users for a sub-directory. Looking at the number of users per country the data seem odd: from row 4 onward all numbers are divisible by 23. Why is that?
You're most probably looking at a sampled report
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I have a Google Analytics event label with high cardinality that I'd like to implement - it is a string that can take on any combination of a finite-but-large number of names in a comma-separated list.
I'm worried mainly about losing data - I found this Analytics Help support page:
https://support.google.com/analytics/answer/1009671?hl=en
...which states:
Reports containing high-cardinality dimensions may be affected by
Analytics system limits, resulting in the creation of a rolled-up
(other) entry in the report to contain the data that exceeds these
limits.
...and am wondering if that would also affect reports without the label included, i.e., reports just looking at unique category/action pairings - would GA still roll-up otherwise-identical into "other" entries if the (undisplayed) labels are different?
Also, am wondering if there would be any hits to performance for similar report types (not looking at labels, just category/action pairings).
Maybe this is just bad practice out of the gate? :)
Google Analytics stores daily, in the processed tables, up to a maximum of 50,000 rows (in Google Analytics 360 the limit increases to 1,000,000 rows, making the problem of data aggregation less frequent). As a result, many combinations of unique dimension values are stored for each table processed every day. If a given table has a larger number of combinations of values of dimensions, Analytics stores the top N values and creates a row of type (other) for the remaining combinations of values.
https://www.analyticstraps.com/valori-raggruppati-in-other-nei-report/
Anyway, I tried a custom report with label and without (same time period) and with label I got (other) while without that dimension I got the actual values.
So the problem you fear does not exist (unless the event action is also high cardinality) :)
when I look in Google analytics under visitors overview there is a line chart that tell me how many users per day I have had. But these numbers does not add up to the ones below that show users, new users, sessions and so on. What does the line chart actually tell me? If I for example export the report to an excel file by day I get a lot higher number of users per day compared to exporting by month which is much lower. Can someone explain the difference. I wanted to know the number of visits to the site per day....
While the trend tells you how many individual users visited the site per day, the "Users" below represents you the de-duplicated count of users who came to the site during the time frame applied.
Example: you visit the same site on 4 separate days during a particular week, the line chart will identify you as a visitor on all 4 days (4 daily users). While the User count below counts you an "one" user for the week.
I mean like, count how many clicks the website since beginning and get their country location.
i already testing Google Analytics API but it requires to input date range, which i want from the beginning but no "Since beginning" or "All data" option available.
will set start date from year 2007 works? any suggestion?
will set start date from year 2007 work
Sure, why shouldn't it. The limit is the number of rows your query returns (10 000 per query. Number of row depends on the number of distinct values for the selected combination of dimensions) and the frequency with which you run your query, not the timeframe selected.
You can test this with the Query Explorer were you can run your metrics/dimension combinations without writing API code, so you can first check if you get the expected results.
I'm trying to get all unique visitors for a selected time period, but I want to filter them by date on the server. However, the sum of unique visitors for each day isn't the number of unique visitors for the time period.
For example:
Monday: 2 unique visitors
Tuesday: 3 unique visitors
The unique visitors for the two days period isn't necessarily 5.
Is there a way to get the results I want using the Google Analytics API (v3)?
You're right that Users aren't additive, so you can't simply add them day by day. There are several ways around this.
The fist and most obvious is that if you've implemented the User-ID you should be able to straight up pull and interrogate the data about which users saw your site on which days.
Another way I've implemented before is to dynamically pull the number of Users from the Google Analytics API whenever you need it. Obviously this only works if you're populating a live web dashboard or similar, but since it's just the one figure you're asking for, it wouldn't slow down the load time by much. Eg. if you're using a dashboarding tool such as Klipfolio, you may be able to define a dynamic data source, and query Google whenever you needthe figure (https://support.klipfolio.com/hc/en-us/articles/216183237-BETA-Working-with-dynamic-data-sources)
You could also limit the number of ways that the data can be interrogated, and calculate all of them. For example, if you only allow users to look at data month-by-month or day-by-day, then you only need those figures.
Finally, you can estimate the figure with reasonable accuracy by splitting it into two parts. New Users are equal to New Sessions (you're only new on your first Session), which is additive, so that figure can be separated out and combined as required.
Then, you could take a rough ratio of new to returning Users (% New Users) from, say, 1 year of data, and use that with the New Users figure to generate an average on any level.
The numbers that are shown within a goal flow node do not match the numbers shown in the table below it in the total row.
Could someone please explain why this is or if these numbers represent something different?
The numbers in the table below are visits. The numbers in the nodes are pageviews. Where you get a loop back from one node to another, you'll notice more pageviews than visits (because one visitor has seen the page twice).