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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 Testing

(Taken from my answer to a question on Linkedin)

I have done 100’s of landing page split tests in Google Adwords over the years – so here is how I do it if I don’t have IT resources in order to set up a test with testing software.

First, if your goal is to see which converts better based on your Google conversion numbers within Adwords than its pretty straightforward to read results. If you are going to have to put back end results to it then you will just need to do some additional work with a spreadsheet or calculator (from simple to complex depending on your sales cycle or conversion $ values, LTV etc.)

So here is how you would ideally do it: Read More→

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May
05

Top 7 Online Testing Pitfalls

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I was going through an old notebook the other day and found this gem from an Online Testing webinar that featured guest Ronny Kohavi, GM of the Microsoft Experimentation Platform.

Top 7 Pitfalls of Online Testing and Marketing Experimentation:

  1. Wrong success metric
  2. Incorrect interval calculation
  3. Using standard formulas for standard deviations
  4. Combining data when percent to treatment varies
  5. Not filtering out robots
  6. Invalid or inadequate instrumentation
  7. Insufficient experimental control
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Categories : Online Testing
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Google Website Optimizer announced this week that there is a potential security issue with their Website Optimizer. The basics of the vulnerability is that it would allow an attacker to execute malicious code on your site using a Cross-Site Scripting (XSS) attack,  but only if the website or browser had already been compromised by a separate attack. Google says that the probability of the attack is low but that you should take the necessary action to protect your site from it.

Google has fixed the bug and any new experiments created on or after December 3, 2010 are not vulnerable. But if you have any experiments running that were created before December 3rd, or that are paused or stopped that were created before that date you will need to update the code.

They have given two options to update your code which can be found here in the Official Google Website Optimizer blog post titled Update Your Website Optimizer scripts to secure your site, but your choices are to either stop your experiments and create new ones, or update the code on your running experiments directly. Google states that creating a new experiment is the simpler way between the two options.

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Categories : Online Testing
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This week I noticed Google has been A/B testing their Business Services page. I always love to see tests that other companies are doing.

Google actually has 3 test pages going up against their control. The major problem I see as a current user of the existing page to log into my accounts is that there is no link to Google Analytics from the test pages (yes I know I could go direct, but I go this route out of habit). But as we all know, the proof is in the data of what works best for the goals they are going after.

Click on the thumbnails to see the full size pages and let me know your thoughts.
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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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