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October 25, 2017

Median Time on Page

  • October 25, 2017
  • 2 replies
  • 12518 views

I am trying to create this calculated metric using the median function in conjunction with time spent per visit, but it is not working. I get the same value all the way down the column, regardless of what date range or dimension i break it down by. I also tried using it with"total seconds spent" but got the same result. Any ideas?

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2 replies

Gigazelle
Adobe Employee
Adobe Employee
October 27, 2017

Hi Shawn, can you give us some info on how you had the workspace set up? If you're able to provide enough info to where I can start with a blank workspace and work up to where I can clearly see all median values being the same, that would be the most ideal.

November 1, 2017

Hi there,

here is an image of how I set up the median time per visit metric. On the workspace, I tried this metric with multiple dimensions, such as last touch channel and referring domain. All of them have the same median time per visit going down the column.

Attached is

Level 2
March 7, 2018

Did you get an answer from Adobe on this?  I have same problem!

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Level 5
September 27, 2019

Basic functions within Adobe Analytics fall into the categories of 'Row' or 'Table', its imperative to be mindful of which type you are trying to employ.

Table Functions versus Row Functions
A table function is one where the output is the same for every row of the table. A row function is one where the output is different for every row of the table.

Median is a 'Table' function.

Couple of ideas to get you close:

1.) Use a cumulative custom metric to evaluate where historically the 50% of visit break point is - then create a calculated metric for % of visits that are that value or lower.  This will allow you to trend if there is a change.

2.) Use nested if formulas to achieve a bucketed version of the median metric.  Something like (if visits shorter than x divided by all visits is > .5 then x)  You will need a number of if statements and need to start with your lower bucket.

There are a couple of screenshots in this tweet that provide direction.
Twitter