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Radically Different Average Time on Site (All Visits vs. Monthly)

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Level 1

I have found and understand the documentation around how Average Time on Site is calculated, however I'm still puzzled by some of the numbers I'm seeing in one of my Workspace dashboards.

 

Typically I keep Average Time on Site nested in a table with individual pages as a dimension, but recently I needed to find a number for this across an entire quarter for the entire site, as well as each month within that quarter. In a new report, I set the quarter in question as the timeframe, and created a new table with just Average Time on Site and used "All Visits" as my dimension. This gave me a total average of around 7 whole minutes. Fishy.

 

Next, I replaced "All Visits" with "Month" and for each month I see an average closer to 1 minute, which seems more realistic.

 

I feel firmly that the 1 minute averages are probably closer to the truth, but before I report these numbers can anyone help me understand why the average gets so bloated using the "All Visits" selection as a dimension? Thanks!

1 Reply

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Employee

@AndrewOlsson This is working as desgined behavior. 

 

I understood the scenario, when "All visits" segment is used it gives different Avg time on site while it gives different value compared with the "Month" dimension

Below is the explaination for you.

Below is the explanation on the same

For example, for the month of July, if we had two visits in the same month, so the sequence will be 1. 
 
July 3
Visit 1
Hit 1 - 10
Hit 2 - 20
Hit 3 - 10
Total seconds spent - 40

July 5
Visit 2
Hit 1 - 20
Hit 2 - 30
Total seconds spent - 50

Aug 3
Visit 3
Hit 1 - 10
Hit 2 - 20
Hit 3 - 30
Hit 4 - 40
Total seconds spent - 100

July-August report


All Visits segment : 

Average Time on site: (100 + 50 + 40)/3 = 190/3 = 63.3seconds

However the normal free form table with Month as the dimension

July = (50+40)/1 = 90 seconds (as it's essentially the same month so the denominator sequence will be 1)

August  = 100/1 = 100 seconds

 

Hope this explains