Forum Discussion

jcabeza's avatar
jcabeza
Frequent Visitor
9 years ago

user measure google analytics

I have wrong data from Google Analytics to PowerBI, they are different than data in Google Analytics in "user" measure.

 

 

 

 

 

15 Replies

  • I would suggest making sure that you are using the identical measure from Google Analytics when getting the data. I am going to assume that the metric you have chosen is slightly different from the one shown in Google Analytics
    • jcabeza's avatar
      jcabeza
      Frequent Visitor

      Is the same measure in the same time period

      • GilbertQ's avatar
        GilbertQ
        Super User
        Interesting the only thing I could think of is there a delay between what is on the Google Analytics site and their cube?

        Do you get matching numbers on a previous day or week?
  • Hi Team,

     

    Please help me out here, even I am facing the same issue with count of users not matching with actual GA users. 

     

    Thanks,

    Ram

    • RolandKramer's avatar
      RolandKramer
      Frequent Visitor

      Hi there,

       

      Same issue for me. This is what happens:

      When I load 'Pageviews', 'Session', 'Bounce rate', etc. it looks all good. The values are identical to what is measured in Google Analytics.

      But when I combine these data with the metric 'Users' or 'Number of sessions per user' all data is wrong. 

       

      This tells me that all data is up-to-date, except the 'Users' metrics, which affects other metrics when loaded in the same sheet. 

       

      Hope this extra info helps. 

      • Ram_DCT's avatar
        Ram_DCT
        Helper II

        Thank you Roland! Let's see if we get any attention from BI Dev team.

         

        -Ram

  • EHas's avatar
    EHas
    New Member

    I'm running into the same problem. I think it may have to do with how GA counts users, it involves their client ID but as far as I can see that's not available when importing to Power BI.

    • Anonymous's avatar
      Anonymous
      Not applicable

      Facing the same issue and understanding how GA works, I can provide an answer but not a solution.

      The fact is that a user is not a summable metric against the days dimension as "users" are actually "unique users". That's because Users on day 1 + Users on day 2 will NOT be equal to Users on day1+2, since there are some users that have been visiting our site on day 1 AND day 2.
      So imagine that on day 1 you have users

      A, B, C

      and on day 2 you have users

      C, D, E

       

      GA tracks users with cookies so it's able to recognize that user C on day 2 was the same on day 1.
      Unique Users Day 1 = 3 (A, B, C)

      Unique Users Day 2 = 3 (C, D, E)

      but Unique Users Day 1 and 2 = 5, not 6 (A, B, C, D, E)

       

      When you run the report for a certain time period in GA, it will count only uniques on the time period, But when you connect PowerBI to the GA and you get the users metric against and the time dimension, it will report you 3 users on day 1 and 3 users on day 2, hence you sum them and makes 6 not 5.


      What could be the solution? Keep in mind that I haven't tested yet:  downloading the user metric but choosing only the week or month dimension instead of the day, so (probably) GA provides the uniques for the week or month, which you can show in your report when the period is week or day. But you really can't count unique users like you do on GA on any time range UNLESS you download each and every occurence of a users with it's "client ID" (GA unique ID), which I don't think it's possible.

      • stiggrr87's avatar
        stiggrr87
        Helper I

        I thing this is correct. When you use different time periods from the GA then you will see the "unique" users for the each selected period. Eq. when monthly view then it matches with monthly view in GA page. 

         

         

        In my opinion, the easiest way to get correct numbers for different periods is to extract separate tables. Daily unique then take the stats by days. But you cannot sum those days, because monthly stats is different then. Its all about how to explain the result then.