Email Marketing and Google Analytics: Add Power, Save Time

Julie Waite

This post is the first in a series on Google Analytics by Chris Casarez, a Google Analytics consultant and employee of Transamerican Auto Parts, a Bronto client.

Google AnalyticsWe all know tracking your email campaigns correctly is extremely important.  How you track emails can spell the difference between having an email marketing channel that can be easily condensed into broad reports (i.e. monthly sales numbers) with campaigns that can easily be tracked separately (i.e. comparing this week’s email to last week’s) vs. a disorganized system that takes time to organize or condense into meaningful metrics.  Using an analytics program like Google’s can be a powerful and time-saving way to get a jump on your data.

Using the Google Analytics URL builder

Google Analytics provides a free URL builder which allows you to quickly create tracking URLs using query string values.  Because you may need to pull different types of reports, it’s important to ensure you are appending your query string values in the proper order.  The three values you absolutely need are Source, Medium, and Campaign. Here is how Google describes these values:

Source
Every referral to a web site has an origin, or source. Examples of sources are the Google search engine, the AOL search engine, the name of a newsletter, or the name of a referring web site.

Medium
The medium helps to qualify the source; together, the source and medium provide specific information about the origin of a referral. For example, in the case of a Google search engine source, the medium might be “cost-per-click”, indicating a sponsored link for which the advertiser paid, or “organic”, indicating a link in the unpaid search engine results. In the case of a newsletter source, examples of medium include “email” and “print”.

Campaign
The campaign dimension differentiates product promotions such as “Spring Ski Sale” or slogan campaigns such as “Get Fit For Summer”.  Entire list of campaign tracking dimensions.

It’s important to note that these values exist within subsets of another. Ideally, you can have multiple mediums with a source, and multiple campaigns within a medium. Because these values exist in a tiered manner, it’s important to categorize them in proper order. Depending on the channels you are currently using, there are 2 really effective ways of ordering these values in your appended query string.

Example 1: ?utm_source=bronto &utm_medium=email&utm_campaign=04-03-09

1- The more likely scenario is that you’re using your ESP as your only email marketing platform.  In this case, it makes sense to list the ESP name as your source (we use “Bronto” in the example), and email as your medium.  This especially makes sense if you’re also using Bronto’s other mediums, like RSS feeds (because then you can have multiple mediums listed under the source of  “Bronto”).

Example 2- ?utm_source=email&utm_medium=bronto&utm_campaign=04-03-09

2- If you send emails using more than one medium (for example, if independent store owners are using their own systems, but you still want to track them as part of your overall email marketing channel), and you’d like to track all email marketing in a comprehensive manner, then it may be useful to list email as your source, and “Bronto” as your medium.

Tiering your campaign tracking in this manner will allow you to easily run broad reports.  For example, if you’d like to know your email marketing revenue for March 09, you can simply select this date range, then click on Traffic Sources then All Traffic Sources, and get your overall monthly visits, revenue, transactions, etc.

Figure 1 - All Traffic

Figure 1: All Traffic

Tag each email as a separate campaign

You can also measure your campaign effectiveness individually, and compare specific email campaigns against each other.  If you send routine emails, it may be best to name your campaigns based on the date of the send itself.

So for example, your query string may look something like this:

&utm_source=email&utm_medium=bronto&utm_campaign=04-03-09

This allows you to track each campaign separately.  If you use a consistent naming convention (like a date), you can filter for specific emails.

Figure 2 - All Campaigns

Figure 2: All Campaigns

Conclusion

Tagging your Analytics tracking strings using a proper naming convention can make your life easier.  In addition to this, an efficient naming convention will allow you to better utilize more advanced features like regular expressions and Advanced Segments (more on this later).

Sources for further reading:
Understanding campaign variables: The five dimensions of campaign tracking
Tool: URL Builder
Installing Google Analytics
Google Analytics – Save time with Regular Expressions

Chris Casarez is a Google Analytics consultant and employee of Transamerican Auto Parts, a Bronto client.  You can read constantly updated Google Analytics tutorials on his website: www.seoracle.com.

4 Responses to “Email Marketing and Google Analytics: Add Power, Save Time”

  1. Hey Julie,
    Nice overview. An extra tip I would enclude regarding the tagging of each e-mail as a specific campaign: if you have for example newsletters and promotional triggered emails, you can use a streamlined syntax for the campaign name. for example nl20090428 for newsletters, and promo20090428 for promotions. What’s cool about this, is that you can filter all results with advanced segmenting in Google Analytics. It’s easy to create a custom segment where you take “campaign” as a dimension, and you use “does not start with” as the condition. For the value you can enter “nl” (newsletters). Now you can compare your total site data to the data without the newsletter, by applying this segment as a custom segment in the advanced segmenting of the Google Analytics dashboard. Another variation would be to take for example “nl200904” as a value. Now you can include/exclude all newsletters send in april 2009.

    Reply
  2. Bart,

    Excellent point on the streamlined syntax. It makes it so much easier to include or exclude data, both for the regular filter and advanced segments. It also means less need for ‘complicated’ use of regular expressions!

    Reply

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