So what it the point of all of this
analytics? Is it to run frequent reports and setup custom dashboards?
Is it to print fancy infographics that tell a story without providing
any real insight? Analysts need to realize that the reason why
companies invest efforts in employing these tools is to simply
generate more money. Sounds obvious. Yet many organizations blindly
implement web analytics tools without developing strategies and
measurements that allow for insight into the effectiveness of
marketing campaigns across all ad networks. Without an effective way
of measuring the ROI of all web based advertisement campaigns,
companies can not gain insight into which techniques are generating
the most money.
Google Analytics provides plug-ins that provide easy ROI reporting for advertisement campaigns that are generated through Google's online marketing tools. Information about advertisement campaigns implemented in Google Adwords can be linked to a GA account to allow for the baked in reporting tools to be used in Adword ROI analysis. But what about other online advertisement campaigns (Facebook,Bing, partner sites)? If the goal is to utilize analytics to make money, then organizations need to analyze which advertisement campaigns are the most effective across all ad networks .
GA provides tools for users that allow for non Google ad network cost data to be uploaded from files (excel spreadsheets) into the GA suite. Uploading daily costs data allows for a one stop web analytics experience where all relevant online advertisement costs and statistics are merged together, allowing for reflection on the effectiveness of specific marketing efforts.
Where to Start?
Before we can start uploading data
into GA, we need to make sure our advertisement links are created in
Google's URL builder tool. Utilizing the builder allows us to
maintain effective management across campaigns, mediums, and
sources[1]. Please refer to Bryce Bagley's excellent post excellent post
on how to accomplish this.
Once our URLs have been built, we then
need to develop a spreadsheet that contains information that will
allow us to track what campaigns we are currently running, what kind
of traffic they generated, and how much they cost. Advertisement
tools outside of Google’s ad network also can provide these same
statistics. Google provides guidelines on what data can be uploaded
and it's format.[2]
Before we can start uploading data
into GA, we need to make sure our data is formatted in a specific way
that allows for Google's API to read it. Companies should format
spreadsheets according to the dimensions and metrics shown in the
table above. However, many companies may have spreadsheets that look
similar to this one.
Google’s data upload API is unable
to read the file due to the titles in the columns being
unrecognizable by the tool. However, it is easy to reformat into a
API friendly file.
How to upload the Data
Before we can upload the data, we must
make sure that our spreadsheet file has been formatted appropriately
and saved in the .CVS file format. This format is an option when
saving files in excel. Once our files are ready, we can upload our
data using Google’s free self service API or an independent GA
application provider for a cost.
Google's Self Service API:
This method involves an intermediate
knowledge of how to utilize API's and a small bit of scripting logic.
Due to this falling outside the realm of this course, I have attached
several tutorials on how to set up API access in Google's developer
tools and how to enable data uploading in GA. [4]
API Demo
Independent Application Providers.
Many companies have developed tools
that allow for easy data integration from excel into GA. These tools
provide the same functionality while providing an easy to use
graphical user interface. A tool provided by Next analytics provides
the ability to pull informaton from the web into excel for analysis,
while another another application by GA DataUploader pushes data from
excel into GA. For more information on applications that provide
additional tools in GA please visit the App Gallery. [5]
GA Data Uploader Demo
Analysis through Reporting
Once the data has been uploaded (which
can take up to 12 hours) we can take a look at the effectiveness of
the campaigns in relation to one another using the built in GA tools.
Organizations must look at ROI
holistically. Viewing a report showing the ROI analysis of a single advertisement campaign only tells you only a part of the story. It is
through the compiling of all advertisement endeavors that allow for
an understanding of how our efforts are effecting the bottom line.
Yet even then, organizations need to continue to revisit the ROI that
the analytics team bring to the table.
References:
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