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Google Content Experiments – Tracking Multiple Goals

10 September 2012 BY

You may be familiar with Google Analytics Content experiments since the projects transition from the former “Google Website Optimizer” project. If you’re not I would suggest reading one of the articles below and bookmarking this Article for later:

One of the current limitations with Google’s content experiments is that you can only track one goal. If your like me then this can cause potential issues as I work with a many sites which contain pages with multiple goals i.e.

  • News letter sign ups
  • Different Forms
  • Affiliate links
  • E commerce Products
  • etc.

Tracking Multiple Goals using Content Experiments

After much research I came across a Google Plus post by +Justin Cutroni (Google) on Multi-Goal Measurement in Google Analytics Content Experiments. This was enlightening to me and so I thought I’d put the principles into practice.

Step 1 – Goals

The most important part of Analytics is making sure your goals are set up correctly. In my experiment I’m using an Affiliate website and so there is no actual goal other than users clicking on one of the ads. So I’ve used event tracking and then created goals based on the events.

Not familiar with this? Then please read:

Step 2 – Pages to test.

In order to test conversion changes you need to create multiple pages against an original, if you unfamiliar with what to test, this article is probably too far down your journey, you will find some useful insights about testing conversion below:

Step 3 – The Content Experiment

If you read the article from Michel Wester you’ll know how to set up a standard experiment, however this time we are going to make a slight change as follows:

There are four parts to setting up a new content experiment of:

  1. Choose Experiment Pages
  2. Set Experiment options
  3. Add and check experiment code
  4. Review experiment

In “Set experiment options” you need to ensure that “Rewrite variation URLs to original in Content reports” is left un-ticked.

If you tick the option then what happens is Google will treat all visits to each individual page (i.e. the variations) as just being to the original page, in our instance we want to make sure they are separated so we can use advanced segments to compare the data.

Step 4 – Setting up Advanced Segments

Now all we do is simply create three custom advanced segments i.e. one for each page:

  • The Original
  • Version One
  • Version Two

If you not familiar with Advanced segments you can create the above as follows:

  • Include: Page
  • Exactly Matching: Your Page location

You’ll need to do this for as many variation pages as you are testing (In this example two variations).

Step 5 – Done

Your set up should now be complete and you simply have to let the content experiment run.

Note: You do have to start the content experiment, although you may not actual use the report it gives you. My personal advise is choose your key goal for the experiment as we will see the overall goals using segments.

Step 6 – Analysis

Now is where the fun starts, can choose your segments against a date range.

Note: Any conclusion you may have will be manual; Google will not tell you “A WINNER” you have to make the choice yourself, however you will see different data to what you ascertain is the overall winning format.

The Results – Step 1

  1. Choose your segments as above.
  2. Choose Goals >> Overview

You will see the goals completed for each experiment page against the original and the overall conversion rate (i.e. Visits v Conversions)

Note: In the example it is showing two days worth of data, this experiment is still running, but illustrate how it works.

Overall Conversion Rate

Analytics will give you an overview of the conversion rate for all Goals. As you can see from our initial data Variation two shows signs of being a winner. (It is too early to be precise).

However remember that this is the overall conversion, you probably want to dig into specific conversion of your individual goals for that page. Well Guess what? We can now do that.

  • It won’t give you the individual conversion rate, but can work this out by exporting the traffic to those pages and the conversions. (Or I’m sure you can create a custom report)
  • We can quickly visualise how many conversions each goal has for each page. (Also we setup in the original experiment to split 100% of the traffic.)

Conclusion

I think being able to track multiple goals is a very good advancement for Google Content experiments even if this is a workaround. Using the above techniques with event tracking will allow you to test more webpages for conversion.

Now its your time to try, let me know how you get on.

AUTHORED BY:
h

Neil started his own consultancy in 2009 of Quaero Media (formerly SEO Mad Ltd) where he works consulting with other Digital Agencies to affiliates or in-house teams. Neil original entered the world of Search in 2002 as the technical mind behind a start up by the name of Just Search.
  • Russell Ketchum

    Content Experiments has new features. You can now access experiments and variations directly and use them to build custom segments. Russell Ketchum – Analytics PM

  • Harshil Adesara

    While the experiment is going on, under the ‘Explorer’ Tab, there are multiple options – Conversions, Site Usage, Goal Set 1, Goal Set 2, etc. you can click on any of them and the the corresponding values for all the goals that you have set!

    Isn’t this easier than creating Advanced Segments?

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    Appreciate your several other superb article. Where in addition might anybody have that form of information in such the perfect method of publishing? I’ve a display a few weeks, that i’m on the hunt for these kinds of information and facts.

  • Chris Hickman

    Are you able to setup multiple goals, I only saw the option to pick one. I know you can make a regular expression to have all of your goals as one goal but it will be hard to tell them apart.

    It looked like in the screen shot you can see the other goals you already have setup in the analytics, is that true?

    If that is true is there any data you lose out by using the standard goals opposed to using the one goal in the experiment?

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