Hi all, 

We have recently joined the wonderful AdWords to BigQuery datatransfer 
beta. Please forgive me, if my question is trivial to you. I'm not an 
experienced data scientist :). 

I've used the table: *AccountStats* to visualise our *Cost, Conversion 
Value* *and ROI* in DataStudio. I am using *Date* as dimension and offer 
the possibility to filter on *AdNetworkType1*. I visualised this in 
Datastudio and checked the total cost for the 8th of May with the AdWords 
UI and that matches perfectly. Great!

The next thing that I would like to do: is show the same visualisation but 
offer the dimension *CountryCriteriaId* as filter. I've checked the AdWords 
Transformation reference guide 
<https://cloud.google.com/bigquery/docs/adwords-transformation> and 
concluded that *Geo Performance Report: GeoStats table* would be best 
suitable. I've duplicated the table in DataStudio and replaced the 
*AccountStats *from BQ with *GeoStats.* Unfortunately the result shows 
highly inflated values. For example: the 8th of May 2018 shows a cost of 
almost x5 higher than our actual cost that day. I've checked the raw data 
in BQ and that shows the same results (although not corrected yet with 
/1000000). 

My question is: how does it come that the summed value based on group by 
date is over 5x higher in table *GeoStats *compared to table *AccountStats*
? 

Any help is highly appreciated. 

Kind regards,
Pim Coffeng

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  • ... Pim Coffeng
    • ... 'Bharani Cherukuri (AdWords API Team)' via AdWords API and Google Ads API Forum
      • ... Pim Coffeng
    • ... 'Bharani Cherukuri (AdWords API Team)' via AdWords API and Google Ads API Forum

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