Hey Google Website Optimizer users! Has August snuck up on you too? I just wanted to send out a reminder that as of tomorrow, August 1
st, you will no longer be able to access Google Website Optimizer and if you haven’t already, it’s time to start using the new Experiments tool in Google Analytics. First, I will discuss some important steps to take in your transition from Google Website Optimizer to the
Google Analytics Experiments tool, and then I will take you through the steps of setting up a test using the Experiments tool so that you can get started right away!
Say Bye to Google Website Optimizer
Put the following things on your to-do list to get done before tomorrow:
1) Make sure to retrieve any data from old tests in Website Optimizer that you want to keep for your records. As of tomorrow you will no longer be able to access those results.
2) Make sure to end any tests that are still running and remove Website Optimizer code from all pages on your website.
3) Make sure that all pages are updated to reflect the content of the winning variations.
4) Make sure to redirect the URL of the variation pages to the main page to ensure that visitors who have bookmarked the variation pages can still access your content.
Say Hello to Google Analytics Experiments
Once you have completed the above steps, it’s time to start experimenting in Google Analytics! In order to find the experiments feature, first select the profile you want to be in, make sure that you are on the
Standard Reporting tab, select the
Content section from the left-hand column, and click the
Experiments option in the expanded Content Section. Once you have made it to the right place, you should see a screen that looks like this:
Step 1: Enter the URL of the page you want to improve and select
Start Experimenting.
Step 2: Choose a descriptive name for the experiment to easily identify what it is that you are testing and choose the variation of the page that you would like to test against the original.
You may add up to 5 variations of the page for testing. Once you input the URL of the page into the correct field, a snapshot of the page should appear to the right.
IMPORTANT NOTE: Make sure the Google Analytics tracking code is on ALL pages that you want to test.
Step 3: Set the experiment options.
In this section of setting up the experiment, you will select the goal within Analytics that you want to use to measure the results of your test. If you do not already have a goal set up for your profile or you would like to set up a new one, you can select + Add new goal. Note that only URL destination and Event goals are supported at this stage. Also, during this step you will select the percentage of visitors that you want to be included in the experiment. You have the option to choose between 100%, 75%, 50%, 25%, 10%, 5%, or 1%.
Also on this page is a box for notes where you can include any important notes about the test to serve as a reminder for yourself or to inform other account users about important aspects of the test that they should know about. You are also given the option to rewrite variation URLs to the original page within Content reports. What this will do is consolidate all traffic to both the original page and the variation page under the original URL in your Content reports in order to keep page traffic comparisons consistent month over month. You will still be able to see traffic to the individual pages within the Experiments report.
Step 4: Add and check the experiment code on the original page of the test.
With the new Experiments feature in Google Analytics, you only need to add one piece of code to the original page, but make sure that both the original and variation pages contain the Google Analytics tracking code for your profile. Once you have verified that the Google Analytics tracking code is on the pages, paste the given experiment code immediately after the opening head tag at the top of the original page.
Once you have added the experiment code, you can select the Next Step button to verify that the code has been added correctly and that each page contains the Analytics tracking code. If everything is correct, you should see green checkmarks next to all pages as seen below:
Step 5: Review your experiment and begin testing!
On the last set up page, make sure that your pages are being displayed correctly and verify that you have selected the experiment settings you want. Once you have confirmed that everything is set up how you would like it, select
Run Experiment and begin collecting data!
For a walk-through of how to create a new experiment, how to look at the data as an experiment is running, and what to do once the experiment is completed, check out Search Mojo’s
Google Analytics Experiments Training Video.
Once you’ve started using the new Experiments tool in Google Analytics, let me know your thoughts about the set up process and new features available. Feel free to comment below or find me on Twitter
@lindskeller.
Step 1: Enter the URL of the page you want to improve and select Start Experimenting.
Step 2: Choose a descriptive name for the experiment to easily identify what it is that you are testing and choose the variation of the page that you would like to test against the original.
You may add up to 5 variations of the page for testing. Once you input the URL of the page into the correct field, a snapshot of the page should appear to the right.
IMPORTANT NOTE: Make sure the Google Analytics tracking code is on ALL pages that you want to test.
Step 3: Set the experiment options.
In this section of setting up the experiment, you will select the goal within Analytics that you want to use to measure the results of your test. If you do not already have a goal set up for your profile or you would like to set up a new one, you can select + Add new goal. Note that only URL destination and Event goals are supported at this stage. Also, during this step you will select the percentage of visitors that you want to be included in the experiment. You have the option to choose between 100%, 75%, 50%, 25%, 10%, 5%, or 1%.
Also on this page is a box for notes where you can include any important notes about the test to serve as a reminder for yourself or to inform other account users about important aspects of the test that they should know about. You are also given the option to rewrite variation URLs to the original page within Content reports. What this will do is consolidate all traffic to both the original page and the variation page under the original URL in your Content reports in order to keep page traffic comparisons consistent month over month. You will still be able to see traffic to the individual pages within the Experiments report.
Step 4: Add and check the experiment code on the original page of the test.
With the new Experiments feature in Google Analytics, you only need to add one piece of code to the original page, but make sure that both the original and variation pages contain the Google Analytics tracking code for your profile. Once you have verified that the Google Analytics tracking code is on the pages, paste the given experiment code immediately after the opening head tag at the top of the original page.
Once you have added the experiment code, you can select the Next Step button to verify that the code has been added correctly and that each page contains the Analytics tracking code. If everything is correct, you should see green checkmarks next to all pages as seen below:
On the last set up page, make sure that your pages are being displayed correctly and verify that you have selected the experiment settings you want. Once you have confirmed that everything is set up how you would like it, select Run Experiment and begin collecting data!
For a walk-through of how to create a new experiment, how to look at the data as an experiment is running, and what to do once the experiment is completed, check out Search Mojo’s Google Analytics Experiments Training Video.
Once you’ve started using the new Experiments tool in Google Analytics, let me know your thoughts about the set up process and new features available. Feel free to comment below or find me on Twitter @lindskeller.
