When I check the website's Users since a certain date it returns a super low value.
The example:
If I want to see the data from 01/01/2016 until 13/06/2021 I get 6 Users, 32.323 New Users, 37.611 Sessions, etc.
The Users number don't make any sense.
However, if I do 01/09/2016 until 13/06/2021 I get 16.849 Users, 16.973 New Users and 22.142 Sessions.
These numbers do make more sense.
So basically, if I consider ANY START DATE before the 01/09/2016 I will always get a super reduced value in the Users part, however, if I consider any start date after, and including, 01/09/2016 I will get reasoable values.
Has anyone ever had this issue?
From 1 September 2016 Google Analytics has brought a new feature, the ability to set the Users metric as the main metric, instead of Sessions. This event has taken the name of Users Everywhere and involves some relationships including Audience Reports and Acquisition Reports.
If the date range includes a period of time, even one day only, prior to 1 September 2016 or around that date, the result is like this:
This is valid, however, if the option to enable the Users metric in the reports , present at the Property level, is active:
Note: Google Analytics Standard properties have aggregated user metrics data since September 1, 2016 while Google Analytics 360 properties started aggregating data from May 1, 2016).
Source: https://www.analyticstraps.com/zero-utenti-con-sessioni/
Related
In a typical GA session, after picking a View ID and a date range,
We can get a week's worth of data like this:
Users
146,207
New Users
124,582
Sessions
186,191
The question is, what BQ field(s) to query in order to get this Users value?
Here is an example query with 2 methods (the 2nd method is commented out).
SELECT
count(DISTINCT(CONCAT(CAST(visitID as STRING),cast(visitNumber as
STRING)))) as visitors,
-- count(DISTINCT(fullVisitorId)) as visitors
I noticed the FVID method was fairly close to what I see in GA (with Users being a little understated by a 3% in BQ) and if I use the commented out method, I get a value that is about 15% overstated as compared to GA. Is there a more reliable method in BQ to acquire the Users value in GA?
The COUNT(DISTINCT fullVisitorId) method is the most correct method, but it won't match what Analytics 360 reports by default. Since last year, Google Analytics 360 by default uses a different calculation for the Users metric than it previously did. The old calculation, which is still used in unsampled reports, is more likely to match what you get out of BigQuery. You can verify this by exporting your report as an unsampled report, or using the unsampled reporting features in the Management API.
If you want the numbers to match exactly, you can turn off the new calculation by using the instructions here. The new calculation's precise details are not public, so duplicating that value in BigQuery is quite difficult.
There are still some reasons you might see different numbers, even with the old calculation. One is if the site has implemented User ID, in which case the GA number will be lower than BigQuery for fullVisitorId. Another is sampling, though that's unlikely in Analytics 360 at the volumes you're talking about.
I'm trying to determine how to calculate the average page depth for all sessions, daily, for a range of dates. I know that GA has a dimension named ga:pageDepth, but this is not the average page depth. This just returns the number of sessions that had a page depth of 1, and 2, and 3 etc. What I would like is something returned like this:
December 1, 2015: 10
December 2, 2015: 9
Where 10 and 9 represent the average page depth for all sessions.
I've been using the Google Analytics API (Query Explorer) but cannot find a way to do it.
Looks like this would be a good job for a calculated metric - that's a relatively new feature in GA that allows you to create your own metric from existing ones.
Go to your account, admin, view settings, calulacted metric, formatting type "float" and formula "{{Page Views}} / {{Sessions}}" (or whatever, there is an autosuggest feature for all metric names you can use). For use with the API there is an "external name" field (which will default to the name field in the name field with the calcMetric-prefix). In the interface this is available instantly after you created it (so it obviously works on historic data), however I'm not sure it will show up in the query explorer (I created a test metric 10 minutes or so ago and I don't see it in the query explorer. However API use is explicitly mentioned in the docs, so it should be available).
In my accounts this is still marked as "beta" so I'm not sure it's already been rolled out to all GA accounts.
Just use the Pages/Session metric. It's already there....
Is it possible to export a list of all page views, with timestamps, out of google analytics?
Currently I can see page views per day, but not specific times for each view. I do see real-time data as it comes in, so I assume the time for each view is being stored.
If not, how might I go about sending that data when I report the page view in a way that will make it accessible in the dashboard?
[[UPDATE]] The Google Analytics v4 API now includes a "dateHourMinute" dimension.
Inside Google Analytics, I think the problem you will run into is that a "timestamp" includes Date, Hour, Minute, Second (and maybe millisec) and you can only drill into one secondary dimension at a time (ie: just date). An alternative method is to use the query explorer or just use the Google Analytics API.
Ad Hoc Report with query explorer
You can use the Google Analytics API Explorer: https://ga-dev-tools.appspot.com/query-explorer/
It will allow you to select:
A date range
Metrics: (like Users, pageviews, etc)
Dimensions: pagePath, Date, Hour, Minute (can't go to second or further, as in a timestamp, though)
Use filters to get rid of some data.
If your website gets a decent amount of traffic (> 50,000 pageviews per month), you might want to grab it 1 month (or less) at a time to avoid hitting limits/sampling effects.
#doctaj solution works. Please just note that if you are using the query-explorer for example, "dateHourMinute" dimension is considered 3 dimensions and will burn 3 spots from your available 7 or 10 dimensions that you can query. So if you need more dimensions, you need to decide which is more important to you. For example, you may want to query for the date and hour dimensions separately to drop the minutes in favour of something else.
If you refer to http://www.google.com/intl/en_uk/analytics/premium/features.html, you will notice that Standard allows for 10 million hits processed per month and Premium allows for 1 billion.
I have a website on an account, with multiple "folders" for different sub-domains, and also different "Views" or dashboards for some of these sub-domains.
The website I am on recently lost tracking for conversion rates, and everything has plummeted to near 0%, which is an incorrect statistic. I am curious as to how I can figure up if this account is reaching the 10 million limit on the standard version. Or at least how to figure actual hits processed a day, week, or month?
Any ideas?
Thanks!
I don't know how Google enforces hit limits in 2015. However in 2013 a Google representative sent one of our bigger clients a document (answering a question about data limits) that contained the following paragraph:
How do data limits impact sampling? Google Analytics does not sample
your clients data at the point of collection or processing, regardless
of how far they exceed our stated limits. So no hits are discarded.
The only way to sample data at the point of collection is for clients
to use_setSampleRate in their tracking code.
[...]
[...] we reserve the right to shutdown their account [sc. if limits are exceeded], but it won't
happen before we have attempted to contact the account Admins multiple times
and we have exhausted all other options.
Unless Google has changed it's policy in the last 1,5 years I would say not, unprocessed hits are not your problem; it seems Google would have contacted you with an request to limit your hits or upgrade to Analytics Premium before problems occurr.
Plus, since you mentioned that you have several views - views do not count towards your quota (they display the same data in different ways). However properties (I think that is what you mean by "folders") do.
Updated 2017: It seems that Google intends to enforce limits more strictly. One of my clients now has the following warning in his GA interface:
Your data volume (XXX hits) exceeds the limit of 10M hit per month as
outlined in our terms of service. If you continue to exceed the limit
you will lose access to future data.
You can create a database table, like this:
visits(
id bigint primary key auto_increment,
ip text,
visit_date timestamp default current_timestamp
)
Upon each page visit, you can insert a record into the table. Later you can view statistics. For instance, visit count in a given day would look like:
select id, ip, visit_date
from visits
where visit_date >= '2015-07-21 00:00:00' and visit_date < '2015-07-22 00:00:00'
Suppose I have 65 people that register on January 1, 2012.
I want to find out how many of those 65 people returned to the site that same week. (More generally, if n people signup on date A, I want to be able to find out how many of those n people return in a given date range.)
Is there a way to do this using Google Analytics? If so, how? I am currently getting the user's username for each page hit.
If you only need to track people who sign in then you don't need to get very fancy. You can copy the relevant user attributes, such as sign up date, from your DB to GA using events or session level custom variables.
But if you want to track everyone, including those who don't sign up, then you'll need to use visitor level custom variables (GA cookies).
I explain how to set this up in detail in this post so I'll just highlight the key points here:
First, decide how to layout the data in Google Analytic's custom variables based on your requirements. For example, are you storing retention dates for daily, weekly or monthly tracking? Do you also want to track cohort goals? Partition this data into the available custom variable slots.
Write the cohort data to these custom variables when visitors arrive or achieve goals using Google Analytic's _setCustomVar function. Setting the fourth parameter of that function to 1 indicates you want to do visitor-level (cookie) tracking.
For each cohort you wish to analyze, create an advanced segment in Google Analytics. Using a regex expression in the condition will give you the flexibility to segment for interesting cohorts. ex: "All users whose first visit was the week before Christmas".
Analyze the results with reports by specifying a date range and the corresponding cohort-sliced advanced segments. Another option is to extract the data using the Google Analytics Data Feed Query Explorer or their API.
Once you've put in the work your new visitors will be stamped by their first visit date and nicely fall into each daily or weekly retention bucket. This is what it might look like if you were tracking weekly retention, for example:
This is not a full solution, but here are some points on how I would approach this problem with the help of Google Analytics:
You have to make sure that you somehow store the registration date of each user, either in your database or in a cookie. Then have a look at Google Analytics Event Tracking. You could for example set up a new category based on the registration date. On every page load in your page, you then have to set up this event tracking call, for example like:
_trackEvent("returns", "2012-01-01", "UserId:123123123")
This way you will receive all page views for users that registered on that particular date. To add a date range in this, you have to make sure that these events only get fired for the number of dates after the signup (e.g. 7 days).
After your date range, you will be able to see how many page views and how many users returned - you even know which users came back.