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/
Related
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'm trying to report conversions to Google Analytics from the server side of an app after a payment is successfully processed. I'm using the Measurement Protocol from the devguides. https://developers.google.com/analytics/devguides/collection/protocol/v1/
The problem is that it successfully shows the goal hits on the real time conversions report, but this are not showed in the normal conversions report as goal completions.
Is there any difference between 'goal hit' and 'goal completion' I'm missing? Or is there any delay on the data that makes into the regular conversions report?
There is a delay. Per documentation it's 24-48 hours (4 hours on a 360 account), although usually the data shows up somewhat faster.
Documentation:
Processing latency is 24-48 hours. Standard accounts that send more
than 200,000 sessions per day to 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 your account sends to < 200,000 per day. For
Analytics 360 accounts, this limit is extended to 2 billion hits per
month.
I used to think there was long delays in data showing up in GA reports as well, until I discovered a small bug in the GA system in regards to time zones. The system automatically selects the date for you on the reports, but if you live in a time zone like Australia or The Philippines, these can be out of sync, and therefore, the most recent data doesn't show up.
I now always set the date to "Today" or to the last few days, and I find all data comes through within minutes, not hours.
I'm currently integrating support for google analytics in my c++ project. I'm still learning how to use the analytics interface, but I can foresee a few potential issues that I may have with debugging.
I'm currently only able to see the "Event Category" and "Event Action" fields for any events in real time. Is there a way to see "Event Labels" and "Event Values"?
I've only been using the analytics interface for a few hours. How long does it take for events to transfer from Real Time to archived events that can be found in the "Behavior" panel? Currently, I'm not seeing any events in the "Behavior" panel, but there are events in the "Real-Time" panel.
If you click an entry in the event category column in realtime view it will give you a breakdown to action and label for that category.
Processing latency is documented here:
Data processing latency Processing latency is 24-48 hours. Standard
accounts that send more than 200,000 sessions per day to 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 your account sends
to < 200,000 per day. For Analytics 360 accounts, this limit is
extended to 2 billion hits per month.
Most of the time the data will show up a lot quicker (in some of my accounts the data turns up within the hour; anecdotally I'd say it depends to some extent on the account size/number of hits. Also for a Premium/360 account guaranteed processing latency is 4 hours). But if you need to rely on it for any business criticall purpose you'd better go for the documented number.
For your title question how to "best" debug, I'd probably start by installing some kind of proxy that allows to inspect the actual request. This will allow you to better track down the cause of the error, if any.
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.
We've noticed lately that as our site is growing, our data in Google Analytics is getting less reliable.
One of the places we've noticed this most strongly is on the "Realtime Dashboard".
When we were getting 30k users per day, it would show about 500-600 people on line at a time. Now that we are hitting 50k users per day, it's showing 200-300 people on line at a time.
(Other custom metrics from within our product show that the user behavior hasn't changed much; if anything, users are currently spending longer on the site than ever!)
The daily totals in analytics are still rising, so it's not like it's just missing the hits or something... Does anyone have any thoughts?
The only thing I can think of is that there is probably a difference in interpretation of what constitutes a user being on line.
How do you determine if the user is on line?
Unless there is an explicit login/logout tracking, is it possible that it assumes that a user has gone if there is no user generated event or a request from the browser within an interval of X seconds?
If that is the case then it may be worth while adding a hidden iframe with some Javascript code that keeps sending a request every t seconds.
You can't compare instant measures of unique, concurrent users to different time-slices of unique users.
For example, you could have a small number of concurrent unique users (say 10) and a much higher daily unique users number like 1000, because 1000 different people were there over the course of the day, but only 10 at any given time. The number of concurrent users isn't correlated to the total daily uniques, the distribution over the course of the day may be uneven and it's almost apples and oranges.
This is the same way that monthly unique and daily uniques can't be combined, but average daily uniques are a lower bound for monthly uniques.