Unable to understand the average figure compared with the number which we see on the graph. Take for instance average engagement time -- what you see on the graph is mostly less than 10 minutes, while the average number which you see on top is > 16m. We are unable to tie these two data points together. We are seeing similar variation for the other 2 buckets i.e. engaged session per user and average engagement time per session. Can anyone help with this?
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I am getting the average engagement time in my analytics dashboard. I want the session time to be displayed in categories based on time:
Sessions less than 1 min
Sessions with 1-3 mins of engagement time.
2 options to accomplish that:
Create Segments for each Session length
Under Segments > Behaviour "Session length" > 3
Aggregate your Data in Excel or Google Data Studio
Can someone explain me the difference between the 2 APP metrics, Active Users and Retained Users. I am looking at these metrics through flurry API and I am grouping my data at month level.
I am not able to understand what is my Retained users number mean at a month level.
Retained users plots two lines. The blue line is the number of users who installed the app in a given month, week or year. The green line identifies how many of these users had at least one session with your app in the past week.
The two lines will generally converge for the current month so use weekly or daily views to analyze the current month.
I have been a happy user of Graphite+Grafana for a few months now and I have been advocating it around my firm.
My approach has been to measure data of interest and collect them into 1-minute or 5-minute buckets and send that information to Graphite. I was recently contacted by a group that processes quotes (billions a day!) and their approach has been to create a log line each time their applications process 1 million quotes. The problem is that the interval between 2 log lines can be highly erratic from 1 second to a few hours.
The dilemma is then: should I set my retention policy to a 1-second bucket so that I can see all measurements associated with spikes or should I use say a 1-minute bucket so that the number of data points to be saved and later on queried is much more manageable. FYI, when I set it to 1-second, showing the data for 8 or 10 charts, for a few days was bringing the system (or at least my browser) to a crawl because of the numbers of data points (mostly NULL) being pushed around from Graphite to Grafana
Here's my retention policy: 1s:10d,1m:36d,5m:180d
Alternatively, is there a way to configure Grafana+Graphite to only retrieve non-NULL data points?
What do you recommend?
You can always specify a lower retention period for 1s metrics so when you show a longer range Graphite will send you only the more coarse level.
For example, you can specify: 1s:2d, 1m:7d, 5m:180d
This way, if you show a range more than 2 days in the past you will get 1m resolution (and so on), which won't make your browser crawl, while you will still be able to inspect spikes in the last 2 days.
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.
GA Unique Visitors data isn't making sense to me. From the GA FAQ we get the following definition for 'Visits vs. Visitors'
"The initial session by a user during any given date range is considered to be an additional visit and an additional visitor. Any future sessions from the same user during the selected time period are counted as additional visits, but not as additional visitors. "
The part that I can't resolve with the GA graph is "Any future sessions from the same user during the selected time period are counted as additional visits, but not as additional visitors". For the graph below covering a 30-day period, I would understand the GA definition to mean that the data represents uniqueness across all 30 days, right? But if you look at the screen shot below, you see a regular pattern for each week over the 30-day period the report covers. From that, it seems the numbers we are seeing associated with each of the days of the graph (e.g. 3.92% (4142) for Tuesday, September 8) is a count of unique visitors just in the context of that one day - i.e. without correlating their uniqueness to the rest of the days in the 30-day period. If the graph actually showed uniqueness across the 30-day period, I would expect the daily numbers to start high in the early days of the period and decrease over the 30-day period as the number of already-seen visitors (i.e. returning visitors) increases, no?
What am I missing here?
UPDATE
Helpful clue from Jonathan S. below got me on the right track.
I think I understand now what the daily bar graph values mean, but it's a little counter-intuitive and I'd bet not what some others might be assuming as well. The reports states "39,822 Absolute Unique Visitors" at the top, which means just that: over the 30-day period we saw this many uniques. Fair enough. The confusing part is that the daily (or weekly) bar values in the graph below are not mutually exclusive uniques as I had assumed, but are values relative only to the 39,822 total - i.e. there is overlap between the unique visitor counts across any group of days. This means the sum of the daily % values > 100% and the sum of the daily count values > 39,822. The algorithm is: when you visit for the first time in the 30-day period, call that "today", you add 1 to the total (39,822) and 1 to the "today" bar value. When you show up again "tomorrow", you are NOT counted again in the total, but ARE counted as 1 in the "tomorrow" bar value.
alt text http://img.skitch.com/20090922-djti81ejj5gqn575ibf8cj1e8x.jpg
I believe it's just an issue of grouping. The top right of the graph has 3 icons to group by day, week, or month. It's currently grouping by day. So if I visit your site today and come back tomorrow, I'll be counted once for each day.
I tried looking at the month view for one of my sites but it didn't give me much meaningful data. I believe the above should answer your original confusion though.
Is it possible that you're searching for something what isn't existing anymore? Unique Visitors/Visits is old terminology. Check: https://www.seroundtable.com/google-analytics-sessions-users-18424.html
Then check how sessions and users are defined:
Sessions ("ex-visits", it's very detailed): https://support.google.com/analytics/answer/2731565?hl=en&ref_topic=1012046
Users in Google Analytics reporting are defined as "Users who have initiated at least one session during the date range". So IMHO it's not about 30 days, it's about the SELECTED date range.
I hope this helps.