I am trying to distribute Pageviews by URL v/s Age as secondary URL, but the result reduces and shows only a set of old URL's but not the new ones.
Here is a report for last 3 years without secondary dimension. This shows 1009 URL's
When added a Secondary Dimension "Age" the results come down to 9 for same period.
I think that age is only applied in certain scenarios where an ad campaign has targeted certain demographics.
What you are likely seeing is the subset of your data that only contains that dimension.
When selecting a dimension, there isn't an "everything else" label unless it is explicitly set, so you won't see the rest of you data - you can assume that "all data minus the age data equals the rest of the data". This is the same scenario as when you set a custom dimension - if you only record the dimension when there is a value (e.g. a promocode on an ecommerce transaction), you will only ever see traffic that has a value applied.
In this instance there would need to have been "no age set" on the dimension, to get the rest of the traffic - which is how demographics work (again slightly unsure). This is like "direct/none" has a default that is put on source medium when there is no source or medium to be discovered.
Thresholds are applied to prevent anyone viewing a report from inferring the demographics or interests of individual users. When a report contains Age, Gender, or Interest Category (as a primary or secondary dimension, or as part of an applied segment), a threshold may be applied and some data may be withheld from the report.
Documentation: https://support.google.com/analytics/answer/2799357?hl=en
My article with test: https://www.analyticstraps.com/i-report-con-i-dati-demografici-non-tornano/
Related
I am working in a project where we need to analyse the data on the basis of users gender and Age. We collect data from firebase to big query. I read some articles that firebase does not collect this data, but not completely sure.
Can someone help me on this?
Gender and age data is only shown in aggregate views in Google Analytics, and even then only when there are sufficient matches for the filter. It is also not exported to BigQuery, for the reasons shown in this documentation page:
Thresholds are applied to prevent anyone viewing a report from inferring the demographics or interests of individual users. When a report contains Age, Gender, or Interest Category (as a primary or secondary dimension, or as part of an applied segment), a threshold may be applied and some data may be withheld from the report. For example, if there are fewer than N instances of Gender=male in a report, then data for the male value may be withheld.
If you need user-level precision for gender/age, consider asking your users for that data, and explaining how you will use it.
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) :)
After spending too much on Power BI trying to see why my user count didn't match when querying userAgeBracket, I used https://ga-dev-tools.appspot.com/query-explorer/ and here is the output:
start-date is 2019-11-01. end-date is 2019-11-30.
Without Date (Notice there are users with age 55-64 and 65+):
When adding Date dimension:
Notice there are now no users with age 55-64 and 65+.
How can I solve this?
As the documentation says:
Thresholds are applied to prevent anyone viewing a report from
inferring the demographics or interests of individual users. When a
report contains Age, Gender, or Interest Category (as a primary or
secondary dimension, or as part of an applied segment), a threshold
may be applied and some data may be withheld from the report. For
example, if there are fewer than N instances of Gender=male in a
report, then data for the male value may be withheld.
So you won't be able in some cases to get granular demographics data in GA reports.
I've been tasked with updating our ecomm tracking but have been told it was not previously implemented with Enhanced Ecommerce because:
... it has limits around number of products. As we have 100,000's of 'Products' due to ... it's not a good fit.
Nonetheless, I am unable to find and conclusive evidence via any (non or official) sources of such limitation/s.
I'd like to upgrade to Enhanced Ecommerce for obvious reasons so does anyone have an idea of limitations around unique product (by id/sku) maximums or anything else?
There's no limit for collecting unique SKUs or other dimensions, but you might have problems during reporting. Limits apply during the processing of high cardinality dimensions, and you might get many of them aggregated as (other) values among your dimensions.
Each report dimension (e.g., Page, Browser, Screen Resolution, etc.)
has a number of values that can be assigned to it. The total number of
unique values for a dimension is known as its cardinality. For
instance, the Mobile (or ga:isMobile) dimension has two potential
values (Yes or No), so the cardinality for that dimension is two.
Other dimensions can have any number of values assigned. For example,
the Page dimension has a different value for every URL that appears on
your site.
Dimensions with a large number of possible values are known as
high-cardinality dimensions. 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.
For further details and actual limits you can check this support article.
Even if these limitations get applied on SKU level, you can benefit from Product Category level reports, and general shopping/checkout behavior reports.
I've installed the tracking code from Google (the updated one, for demographics data), already validated the code and it worked, also enabled it in analytics settings. Problem is there is no data at all, and it's been set up for a week now. When I validated the code analytics said it'll be a day until I see data.
Any idea what's going wrong?
All other data is fine, just demographics missing.
These data won't be showed if you don't have enough users. Can it be the case?
Data thresholds
Thresholds are applied to prevent anyone viewing a report from inferring the demographics or interests of individual users. When a report contains Age, Gender, or Interest Category (as a primary or secondary dimension, or as part of an applied segment), a threshold may be applied and some data may be withheld from the report. For example, if there are fewer than N instances of Gender=male in a report, then data for the male value may be withheld.
These thresholds are system defined, and you cannot adjust them.
If a threshold has been applied to a report, you will see a notice below the report title.
About Demographics and Interests