3 Simple Ways to Import Cost Data into Google Analytics

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If you use multiple ad services and platforms to promote your products, you think about combining all ad data in a single interface to save your time (no switching between tabs) and to compare the evaluation of all campaigns in one system.

As an example, you can combine the necessary information through data import into GA to track the effectiveness of each ad.

How to collect data on ads expenses for Google Analytics

If you want to obtain data import from Google Ads into GA, it won’t be that difficult. There is a natal integration among Google Platform services.

But can google analytics import cost data from other ad networks? Here the question is no.

When it comes to other ad platforms, the challenges might arise. There are several ways to overcome these challenges:

  • Hand-operated import through the GA interface.
  • Get the necessary data with a certain add-on for Google Sheets.
  • Use an out-of-the-box solution.

By the way, each of these options doesn’t need any help or support from IT specialists.

Also, bear in mind that you need accurate UTM tags in your campaigns:

  • Required: utm_source, utm_medium, utm_campaign.
  • Optional: utm_term, utm_content.

Now let’s take a close look at each of our 3 mentioned options.

1. Hand-operated import of data on ad expenses through Google Analytics

If you obtain only a couple of channels for promotion and you want to see the information on their effectiveness every month, this method is great. But once your number of platforms increases, it might get pretty chaotic, problematic and dull.

There are 3 phases to manually import data on expenses to Google Analytics.

Phase 1. Make a data range in Google Analytics.

Click in Google Analytics Data Import on the Admin panel and choose to Create.

By the way, if there’s a need to get essential data from different sources with the same structure, you can use a single data set.

Then click on Cost Data and Continue.

Give a title to your data range and pick the GA view to transfer information on expenses. Click Continue.

Then you need to establish a data set structure by picking the parameters to import data to Google Analytics. There are three required fields, which you don’t fill manually: Date, Source, and Medium. There’s also a set of fields that require at least one parameter: Clicks, Cost, and Impressions.

The third set of fields is available as a choice — you’ll be able to add any additional information you harvest with UTMs — for example, keywords or advertising content.

Phase 2. Make a CSV file to transfer.

As soon as you create the data range, you need to get a CSV file ready, fill it with your data on expenses, clicks, and other metrics from the advertising platform, and download it to Google Analytics. Remember to stick to the same data structure in the CSV file as in the data set from phase 1. If you have some doubts about whether you’ve properly built a file for uploading cost data in Google Analytics Help.

Phase 3. Download the CSV file to Google Analytics.

For this phase, your data should be already gathered and the CSV file is also ready. Only after that, you can send it to Google Analytics. You need to go back to your page on Google Analytics Data Import and pick the Upload File.

Choose the CSV file with the data on expenses on your computer and approve the Upload.

2. Get the necessary data with a certain add-on for Google Sheets

If you already uploaded information on ad expenses in Google Sheets, you can avoid the problems with CSV files. Just use the free OWOX BI Data Upload Add-on and send your cost data from Google Sheets to Google Analytics automatically. If there are any mistakes in the uploaded data, the add-on will advise you on how to correct them.

To import data with the OWOX BI Data Upload Add-on, you need to create a data range in GA and set up the add-on. Then, open an accurately structured cost data table, and click on Add-ons — OWOX BI Data Upload — Upload data.

Now pick the account, web property, and data set in Google Analytics to upload data on costs and click Verify & Upload.

3. Use an out-of-the-box solution: upload cost data automatically via special services

Uploading data manually can take way to much time and human resources for big companies. But no worries. There are services to manage this challenge. They really help marketers and analysts get rid of monkey job and save lots of time. Here’s our solution for this problem — OWOX BI Pipeline.

For now, you can use BI Pipeline to automatically import data to GA from Facebook, Instagram, Criteo, Trafmag, Bing Ads, Twitter Ads, Yandex. Direct, Yandex.Market, Yahoo Gemini, MyTarget, AdRoll, Sklik, Outbrain, and Hotline.

OWOX BI can also expand shortened links, recognize dynamic parameters in ad campaigns, check UTM tags, and notify you of any mistakes in tags. And the cherry on top is that Pipeline converts the currency of the ad service you use to the one in GA.

So in order to use this service, first of all, you need a data set in GA and then set up OWOX BI Pipeline using your Google account.

When you’ve done that proceed to the next steps:

  1. Navigate to Pipeline, create a pipeline and select the data source.
  2. Next, provide access to the advertising service.
  3. provide access to your Google Analytics account.
  4. Select the data set in Google Analytics to upload cost data.
  5. Pick the starting date for uploading data. You can change this to a past or future date.
  6. Now select a view and click Create.


Voila — the pipeline is ready to go. Easy enough, huh?

Wrapping up

In order to monitor the efficiency of your advertising channels, you should compile data in a single system like Google Analytics. For sure the easiest way to do that is to automate the whole process with services like OWOX BI. But that’s your choice.

For example, if you are aware of how to code, you can use a semi-automatic approach of uploading data with the help of Apps Script and the API from your advertising service. Go ahead and read more about this method on Ryan Praskievicz’s blog and on Google’s official site for developers.

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