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Welcome to Josh Baker's Practical Advice for Optimizing Your Internet Marketing blog. Here you will find internet marketing optimization and online strategy articles full of tips, tricks, discussions, and thoughts to help you take your marketing and business to the next level of success.

Archive for Online Conversion Tools

Using Minimum Viewing Time as a A/B Test Conversion Goal

Sample Scenario:

  • You want to add a page with a video or demo to your web site.
  • You believe that it is important for visitors to view as much as possible of the video.
  • You have 2 videos to test against each other, and your test goal is to determine which one of your videos keeps more visitors watching (engaged) for at least a certain period of time and plan to  keep the one that engages viewers more than the other.

In this scenario, since your test goal is to determine which video users are more engaged in watching for at least a certain period of time you will therefore want a conversion to trigger and to be recorded in GWO after that set period of predetermined minimum viewing time.

Back to the Scenario:
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Back in April I posted my 4 Items for My Google Website Optimizer Wishlist, and the 2nd bullet on my GWO wish list was:

  • Ability to add notes to tests – it would useful to be able to make notes about tests within the test admin itself for each test. Many times we have multiple people looking at a test and I would like to leave comments and get responses within the test, not only for ease but for permanent documentation

Today, Trevor Claiborne of the Google Website Optimizer team posted on the GWO Blog that they have added the ability to add notes to your GWO experiments. I am so very excited as this should really help out with collaboration and to help others who like to look at the current status of tests we have live as even the documentation for past tests. Although I already have a reliable system for test documentation this should help decrease the amount of cross-referencing and multiple email responses to others (I hope!) that now can easily be documented within the test itself.

Thank you Google Website Optimizer team!

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Interpreting the Estimated Conversion Rate Range Properly in GWO is of Key Importance!

It’s easy to get initially excited when you see that one of your test panels in Google Website Optimizer has a higher Estimated Conversion Rate than that of your control panel as presented on the Combination Report page. This may even lead to you believe you can end the test (prematurely I may add).

Unfortunately, just looking at the Conversion Rate number given to you by Google in the bold type font isn’t enough, you most certainly need to do a little bit of visualization to really have a better understanding of what is going on and how they are performing against each other.

Whether you are running an A/B test or a multivariate test, this is important to know for either – the number they give you is a conversion RATE RANGE. Many people mistakenly look at just the number given and do not visualize the full conversion range given along with it (done so with simple addition and subtraction of the number given next to the estimated conversion rate after  the plus and minus sign). This range is based on the observed conversion rate of during the experiment thus far. Not factoring this in can lead to many people ending or wanting to end tests before they are truly ready to be ended. For example,

Estimated Conversion Rate

  • Test Panel – 6.0% +/- 1.0%
  • Control Panel – 5.5% +/- 1.0%

Reading and interpreting this correctly would actually tell you that the:

  • Test Panel is converting in the range of 5.0% to 7.0%, and the
  • Control Panel is converting in the range of 4.5% to 6.5%

This being true, their conversion rate ranges are overlapping each other.  Visualizing this information shows you the overlap much more clearly as shown below:
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Jul
21

Online A/B Split Test Calculator

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Are you running an A/B split test for a marketing, email, ppc, or direct mail campaigns and want to know if you have a statistically significant winner to go live with? I recently built a quick and easy online A/B split test calculator at www.SplitTestCalculator.com that will answer this exact question for you.

Please make sure that when you fill out the calculator with your test information that you then click on the calculate results button and look below it in the results section to see if you have a winner or not.

If the A/B calculator says that you have a winner, you can determine the winner very easily by just looking at the conversion rates of  each of the panels and the one with the better conversion rate is your winner. If the A/B split test calculator results declare that you don’t have a winner then you will need to run your test longer, or run a different test.

You can try out my online A/B split test calculator at www.SplitTestCalculator.com .

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Google Website Optimizer, the free multivariate and AB testing tool makes available to you two results reports when you are running a multivariate test; the Combinations report, and the Page Sections report. The Combinations report is easy to read and interpret for the most part (for simplicity purposes here, the pages are listed in order of best performance, and a statistically significant winner with a 95+% confidence level over the control will be highlighted in green), but the Page Sections report many people incorrectly use the data that is presented or are confused on what the report is actually providing. You MUST know how to correctly interpret this report; otherwise you could incorrectly make decisions from the data that can cost you potentially big-time down the road.

The Combinations report provides you with the performance data for all of your page combinations that you are testing and compares each page combination to your original page (the control) in order for you to determine what test page combinations are outperforming the original.

google website optimizer combinations report

The Page Sections report on the other hand displays all of your page sections that you are testing and the elements within each section in order to show you the best performing page element for each particular section.

google website optimizer page sections report

Here is the scoop on the Page Sections report.

Many times, when you are running a test you will notice that the best performing elements according to the Page Sections report are not the same elements that are present in your winning page combination. It’s not as simple as looking at the different sections and choosing all the “best” elements according to Google Website Optimizer Page Sections report and then rolling out a page that contains these elements. The reason being is that the performance of the elements in each section being tested as shown in the Page Sections report are not being calculated and presented in context with the other sections. By this I mean that the results of each element in each section are presented by how they performed against the other elements in that same page section. It’s not taking into account the context of all the other elements on the page when showing you the best performers. To see which the best elements are in proper context, view your Combinations report and look at the individual elements in your top performing page combination.

Confused?

Let me give you an example. If you are testing a main headline, and have 3 different versions:

  • Control/original headline
  • Test headline # 1
  • Test headline #2

And the report shows that test headline # 1 is the best performing element in that area, it’s only reporting to you that between those 3 headlines, headline #1 is the best performer, but it is not taking into consideration how it interacts with the other elements on the page. It’s not saying that for the page you are testing, headline #1 is the best to use for the roll-out page, but instead – between those 3 headlines, headline #1 is the best performing if you are comparing just the performance of the headline itself. Headline #1 might perform the best out of the 3 headlines when compared to each other out of context with the rest of the page elements, but Headline #2 might perform the best in combination with all the other elements and therefore is the one you want to roll out with (but not necessarily reported this way in the Page Sections report). So please, don’t use the Page Sections report to pick out which elements to roll-out live with.

The Relevance Rating graphic (currently found to the left of each page section), alerts you to how much impact each section had on your test (as defined by your test’s conversion goal). It’s presented as a range, from 0 to 5, with 0 representing that the section had virtually no impact on conversions and a 5 as having a high impact on page conversions.

So while the Page Sections report is important to look at to understand what is happening between the different elements in the page sections themselves, and the Relevance Rating is important to look at to understand what page sections are providing what level of impact to page conversions, you should ideally only use this information to help you gain more insights into the test. Insights that will also give you further help in planning future testing of the page.

However, you will only want to roll-out the panel that is deemed the best performer according to the page Combinations report. Of course this is after you finish running your head-to-head follow-up test between your control and the best performing page combination to verify your results outside of the multivariate testing environment!

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