Every RealTime metric is on my website is showing only 4-5 active users (expected) yet my real time count is 90+ (highly unlikely)?
What exactly would cause this? Bots?
Related
which one of the following is correct in the Google Analytics dashboard?
The "Right Now" or the "Metric Total"? how many users I actually have??
It is a bug of Google Analytics real time report.
It has been observed that the inflated number of active users, after a more or less expanded period of time, returns to normal, and then eventually resumes the anomalous count and subsequently re-enters the ranks again.
What probably happens is an accumulation of the number of active users over time without, however, the total being decreased once the user is no longer in that state.
https://www.analyticstraps.com/bug-numero-anomalo-di-utenti-attivi-in-tempo-reale/
Looking at Google Analytics Real Time tracking.
Why is there such a difference in the two numbers?
It is a Google Analytics bug, it is an accumulation of the number of active users over time without however the total being decreased once the user is no longer in that state. There is nothing to do, it realigns itself.
https://www.analyticstraps.com/bug-numero-anomalo-di-utenti-attivi-in-tempo-reale/
I would like to measure how long (on average) users are performing certain actions in my app. For example, the time it takes for a user to add an item to the cart till the time to purchase the items. Can Firebase analytics track these time differences? If so, how can I get a report out of it or add it to my dashboard.
I know this can be done using traces in Performance monitoring, but I want to know these time differences not to troubleshoot performance issues but rather behavioral issues for my users.
Background:
I have a Google Analytics account using which I am tracking user activity for web and mobile app. After logging into your account and choosing the web property and the corresponding view, you generally see a dashboard with quick stats like Pageviews, Users, Sessions, Pages/Sessions, Avg. Session Duration, Bounce Rate and percentage of new sessions. You can change the time period (from the top right area of the Dashboard) to get the same stats for that period.
Problem:
Last week, I was interested in the three main stats: Page views, Users and Sessions for a particular day - say, day A. The dashboard showed the following stats:
Pageviews - 1,660,137
Users - 496,068
Sessions - 983,549
This report was based on 100% of sessions.
I go back to the dashboard TODAY and check the same stats for the same day A. Here's what I saw:
Pageviews - 1,660,137
Users - 511,071
Sessions - 1,005,517
This report is also based on 100% of sessions.
Nothing was changed in the tracking code for the web and mobile app. Could someone explain why I have this difference in the stats? Is this normal?
They need some time to update the system, otherwise their system would overwhelm
When you first create a profile it can take up to 48 -72 hours for it to start showing data.
After that time data will appear instantly in the Real-time reports.
Standard reports take longer to finish processing. You need to remember the amount of data that is being processed. Some of the data may appear in the standard reports after a few hours. The numbers have not completed processing for at least 24 hours, so anything you look at then will not be accurate.
When checking Google Analytics never look at todays or yesterdays numbers in the standards reports, if you want accurate information. Things get even more confusing when you consider time zones. When exactly is it yesterday? I have noticed numbers changing as far back as 48 hours. But Google Says in there documentation 24 hours. I am looking for the link in the documentation will post it when I find it.
Found it: Data Limits
Data processing latency
Processing latency is 24-48 hours. Standard accounts that send more
than 200,000 sessions per day to Google Analytics will result in the
reports being refreshed only once a day. This can delay updates to
reports and metrics for up to two days. To restore intra-day
processing, reduce the number of sessions you send to < 200,000 per
day. For Premium accounts, this limit is extended to 2 billion hits
per month.
So try doing the same thing again today but check your last day being Monday. When you check again next week the numbers should be correct.
I've been using a SSIS Integration component to download data from Google Analytics in order to keep an historical view of some websites and track the evolution of them. Basically the metrics we track are Visits (now Sessions) and Visitros (now Users), and the dimensions are Year and Month. However, today I noticed that the data I downloaded for july had a variation on the Users metric. I heard that google analytics uses an estimation method to "calculate" some (if not all) of their metrics, could it be that after that they "adjust" the data with more acurate information? If so, is this mentioned in the documentation? (a link would be highly appreciated) Since the users are complaining that we are not delivering the real GA Data. I tried looked on the Google analytics documentation page with no luck.
Thanks for your time.
PS: Sorry for my english, it isn´t my native language
If you are using the standard version of Google Analytics (you'll know if you are paying $150k for premium), data is sampled depending on volume. Have a read of this article can-you-trust-your-google-analytics-data
I have seen very slightly differing results being returned if you repeatedly call the api with the same historical parameters repeatedly. In my case the figures only differed by 1-2 over a daily set of several thousand, but nevertheless it differed.
If you want to guarantee your results, consider upgrading to premium
Sampling could be an issue if what you are requesting is over 50,000 rows for the time period you are requesting. To avoid it you can download more often, such as daily.
But I think your issue is that there is a processing time for Google Analytics - if you are downloading at 3 am on the 1st it is probable that the processing for the previous day has not finished.
Google Analytics Premium SLA is for 4 hour data freshness, so even that would have trouble. Pragmatically you should allow 24 hours before you download data for the previous day, 48 hours for e-commerce data.
Thirdly make sure it is not Unique Visitors you are requesting, as this is dependent on the time period you are requesting.