easy-button

Media Optimizations Made Easy

  |  July 21, 2014   |  Comments

A look at how Google Analytics made it easier than ever for marketers to quickly and effectively gain insights into their marketing campaigns.

In one of my early blog posts for ClickZ, I wrote about features to use within Google Analytics to more efficiently access your data. What I want to talk more about in this post is the fourth item of the previous post, Cost Data Uploads. The feature holds a vast amount of potential for paid media teams, both online and traditional.

Cost Data Uploads possess this value by giving media teams the ability to directly tie campaign costs to outcomes, in one interface. Within a matter of seconds, marketers can see where their return on investment (ROI) is greatest, where they are lacking, and easily further segment into each group based on dimensions, such as location, device type, operating system, etc.

But, I've talked about this topic once already, so why again you ask? Well, recently Google announced the ability to perform Cost Data Uploads directly from the Admin interface. This has greatly reduced the previous barrier of needing to leverage the Google Analytics API to upload the data, and Google has also updated a few things, such as being able to upload multiple dates within one upload.

What this means for you, the marketer, is you can now achieve deeper insights than ever before, within about 30 minutes. So without further ado, if you are ready to optimize like you've never optimized before, here is a step-by-step guide on how to successfully upload cost data within Google Analytics:

1. From the Admin interface of Google Analytics, select the "Data Import" link under the Property to which you want to upload cost data.

universal-analytics-step-1

2. Within this section, click on the "+New Data Set" button and then select "Cost Data." Don't worry if you see a different amount of options than in the screenshot below. If your account is not yet upgraded to Universal Analytics, you will have a lesser amount.

universal-analytics-step-2

3. Once you proceed to the next step, provide a name for your data set and select the views within the property for which you would like this data imported.

4. Step four, and nearly done. From this section select the schema (dimensions and metrics) that you would like to import, beyond the minimum requirements. The schema you select will be tailored to the marketing channel you are using, the data you have available to import, and what data you need to perform optimizations. Here, I have selected what I find helpful when optimizing paid search campaigns, but again, your schema may vary.
Once you have your schema set up, click the Save button.

universal-analytics-step-3

5. The last part of the configuration setup is to click the "Get schema" button, which will let you download an Excel template, and then click "Done."

6. Now to actually import the data. Export your data from your various channel sources and fill in the data in the corresponding columns of your template. When you have your data in the properly formatted template, click on the Data Import link again from the Admin interface and click the "Manage Uploads" link to the right of your data set. From this page, upload your csv file. You should receive a status of Pending until Google Analytics has been able to process your file.

universal-analytics-step-4

So there you have it, six quick, pain-free steps to gaining access to extremely valuable information for your media campaigns within Google Analytics. Once you have this information imported, start using it within the "Cost Analysis" report suite under the Acquisition section.

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ABOUT THE AUTHOR

Robert Miller

Robert Miller is a Senior Analyst at Search Discovery. He is actively involved in industry organizations, such as the Analysis Exchange and the Digital Analytics Association.

With the Analysis Exchange, he helps non-profits capitalize on their website data, and educates aspiring digital analysts about the foundation of digital analytics, from the implementation of a digital analytics tool to performing analysis and making data-driven recommendations for organizations.

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