I have two puzzling cases in GA which I hope someone can enlighten me on.
1) Under Audience->Overview, why does the figure under All Users (Fig 1) changes when a new segment is added to the report (Fig 2)?
(Fig 1)
(Fig 2)
The new segment does not have to be new/returning visitor; the All Users figure changes on other segments as well. Note that the Sessions and Pageviews under the All Users segment do not change (correctly I believe).
Is this a bug in GA?
2) Using the same report with additional segments, why is the Number of New Users different from the Number of Sessions by New Users (Fig 3)?
(Fig 3)
As explained by this post, a new user who visits the site a second time will be counted as a returning visitor, so his second and succeeding sessions should now be counted as sessions being done by a returning visitor.
Doesn't this mean that the number of new users should be the same as the number of sessions done by new users? Are there exceptions (perhaps using a different browser or device) that will skew the results?
Thanks
1 per Eike's comment - including segments causes the numbers to be recalculated and may be slightly different from the precalculated report numbers.
2 is caused by sessions overlapping midnight. GA creates new sessions, and they have the same user and 'New User' flag associated with them, so it looks like 2 sessions with 'New User' settings but it is only 1 user.
Related
I’m wondering if anyone can help me. I’m currently working on a project which involves trying to understand customers who have abandoned one of the stages within a checkout but then returned to the site at a later stage and converted. I would then break this down to the number of days before they returned. I’ve tried creating segments however the data doesn’t seem to be making sense. Has anyone any idea how I’d go about this? Is this even possible in GA or is this something I can only accomplish in BigQuery if at all?
Your help will be very much appreciated.
Google Analytics(GA hereafter) is counting a visitor as a new or returning user by persisting cookie values in client side(in the browser). So once a user is visited, It stores an id which is specific to that user (actually this user means the browser which had been used to visit the website). So when a user visits the site for the first time, GA will store a specific id in a GA related cookie in the client side. If the user visits the website again later in another session, then GA check if there is a client.id for that user stored in the client side. If it found then that user is count as a returning user or New user otherwise.
In Google Analytics, goto Audience -> User Explorer. In there you can see an aggregated view of each user(client.id) interacted with your website and clicking on one client.id will show each user's activities with the website(differentiated by sessions) and will show all the sessions related to that user with the information like time, URL and some other dimension values.
Also if you want to separate out New users or Returning users from each other, you can create a new segment with a condition checking for the User Type dimension against the values "New Visitor" or "Returning Visitor".
To measure returning customers after an abandonment and converted, you can create a segment as follows,
It seems that it's not possible in GA.
There are no metric like "Days between abandoned funnel and conversion" (only "Days before transaction" - between acquisition day and transaction day). So you need a date for abandoned funnel and a date for conversion separately: i.e. you need two reports.
I know solution, but Excel or smth like this is needed if you want to calculate days before conversion.
At first you need to have Client ID as a custom dimension.
Then create custom report contains dimensions Client ID and Date and metric [Your Goal] Abandoned Funnel (Goal with Funnel needs to be set).
And the second report - Client ID, Date and [Your Goal] Complection.
And to merge these tables using Client ID parameter.
Chart from Google Analytics
As I worked on my sites monthly report for visits/trends, I noticed that the user number provided in text (value 4539) is different the the number you get when you add each day's plot point together along the blue line (value of 5110). I have the graph set for users, and also made sure the time frame for data was the same, but I am not sure what why these numbers differ so much.
Can someone explain this to me? Apparently I am an idiot.
Edit #1: This is the default settings under Reports > Audience > Overview. I have no dimensions added or anything more than just the strictly default settings.
User numbers are time dependent. That is to say, a user may come back more than once in a month, and GA knows that because it's detecting the cookie dropped in their browser. So, if Person A visited your site on Monday he counts as one user, and a report for Monday counts him as that. If he comes back on Tuesday and you look at a user report just for Tuesday, he is again one user. So, in individual daily reports Person A is counted as one user, in 2 reports. If you look at a report for the week, he counts as one user, because GA knows that he was person coming back to your site twice in one week.
I would like to compare some data between a 3rd party analytics tool and GA.
Now I would love to see the IP addresses that Ga is receiving however it seems that they do not reveal this information, fine, however, I cannot find a way to use the flat table in the GA custom report to show me the following if possible;
Full Date Time (Seems as though they don't want you to have this either)
Browser Version
Browser Width & Height
Page (from the hit)
And I would like this data not to be grouped by the metric, this way I can see that if the same user has hit a page 3 times it isn't grouped.
If anyone can help please let me know. If the question is poorly phrased please let me know.
Thanks,
Connor.
This requires some work, and it will allow the breakdown only for future hits, not for hits that are already collected.
To view individual hits you need to create a hit based dimension that is unique per hit. Unless your page has an amazing amount of traffic a timestamp in milliseconds (e.g. new Date().getTime()) will be sufficient (for your report you might want to format that in a nice way). So in the admin section of your GA property you go to custom definitions, create a hit scoped custom dimension, and then modify your pagecode to send the timestamp to that dimension. Hit scoped means it is attached to the pageview (or other interacton hit) it is sent with.
If you want to break down your report by user you need the clientid (clientid is how Google recognizes that hits belong to the same user). Again, send it as a custom dimension.
This does not tell you how many sessions the user had (there is no session identifier in GA). If you need to know that you can create a session scoped custom dimension and send a random number along ("session scope" means that GA only stores the last value in a session, so you don't need to maintain a session id over multiple pageviews, since the last value will be set for all hits within the session). The number of different sessions ids per client id then tells you the number of sessions per user.
The takeaway is that GA only shows aggregated data, and if you want to defeat this mechanism you need to throw data at it that cannot be aggregated further. You might run into other constraints (i.e. there is a limited number of rows per report).
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.
We have a way to fetch the number sessions unique per device and the number of The New Feature uses, this can be done with a public API and requires implementation of two events to be sent by mobile applications to Google Analytics server. It will give us a statistics of the sessions when The New Feature was used, although it doesn't directly reflect individual users activity.
Ex: the app was opened 1000 times among all unique users (devices), The New Feature has been opened 200 times, the resulting value is 200/1000 or 20%. The drawback is that at this particular case we have no way to tell that is wasn't one user who has opened The New Feature 199 times and another one who has opened it just once, the real retention rate is low to none.
The secondary statistics that we are aiming to be able to calculate is the percentage of unique users who have used The New Feature at least N times during the given period. This statistics should be a closer representation of the real The New Feature retention as it will both show the share of users who were using the feature and the dynamics of frequency. For that we are not clear of which events are needed to be set up.
Ex: the app was opened 1000 times: user A used The New Feature 10 times, user B 5 times, user C 4 times, most of the other users who used The New Feature opened it 2 times - The New Feature was opened 200 times in total. The resulting percentage of users: 10% have opened The New Feature at least once, 8% used it at least 2 times, ..., 1% used it at least 10 times.
The numbers from the second example are giving us more useful information about how often the new feature is being used, but it isn't clear how we can set it up. We would need a kind of the event that shows a number of uses of The New Feature unique by the users (not just sessions) and I think the event values might be used to distinguish the users, will it be possible to get the number of unique users who has triggered the event at least N times this way ? Any other suggestion is welcome.