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TERMINALFOUR t44u 2010 - WEM Variation impact analysis

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  • 06/12/11
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  • Transcript

    • 1. Raphaele Beyssac Variation impact analysis - A/B Testing Testing your content t44u User & Partner Conference 2010
    • 2. What Is A/B Testing?
      • A/B testing allows you to measure the most successful variation of a page.
      • This variation can be a subtle difference in text, colour, design or could be a very different structure.
      • Using Site Manager you can easily:
        • create the variations,
        • add the code to measure the impact,
        • implement the most successful variant after you have completed your testing.
      • Today we will cover a simple method that can be used to conduct A/B testing.
      t44u User & Partner Conference 2010
    • 3. Method
      • In our example, we want to find out which is the best label for a pdf download link.
      • This method uses code on a landing page to randomly show users version A or version B of a page.
      • Each of these versions show a slightly different label for the pdf download link.
      • Results can be seen in Google Analytics interface.
      t44u User & Partner Conference 2010
    • 4. Step 1 – The Structure
      • A “Marketing Campaign” section (our landing page).
      • Two sub-sections with slightly different content (our 2 variations).
      • View Site Manager Site Structure >>
      t44u User & Partner Conference 2010 Landing Page Option A: URI = variation-a Option B: URI = variation-b
    • 5. Step 2 – The Landing Page
      • We added a piece of code to the “Marketing Campaign” section to randomly display content of “Whitepaper 1” or “Whitepaper 2”.
      • It is also possible to have 10% of users see one variation and 90% another
      • What ever the version of content, the page always show the same URL, i.e.: http://www.my-site.com/news/marketingcampaign/
      • We use Server Side (PHP/JSP/ASP.NET) A/B testing code added as template to the Landing page section
      t44u User & Partner Conference 2010
    • 6. Step 3 – The Variations
      • We created content for option A in the “Whitepaper 1” section.
      • Then it can be duplicated to the “Whitepaper 2” section and slightly amended to create the option B.
      • See the landing page >>
      t44u User & Partner Conference 2010 Option A Option B
    • 7. Step 3 – The Variations Pages
      • Our Goal: find out which link label works better
        • Which file is downloaded the most: pdf in Option A or Option B?
        • Google Analytics: Events Tracking/Goal Tracking can help us find out.
      • For our test we did:
        • Set up a Google Analytics account and added the relevant JavaScript Analytics code to our style header.
        • Update the media formatter so that the media can have an onclick attribute.
        • Add onclick attribute to the pdf links:
        • Option A: onClick="_gaq.push(['_trackEvent', 'Downloads', 'PDF', 'W hite Paper A ']);"
        • Option B: onClick="_gaq.push(['_trackEvent', 'Downloads', 'PDF', 'W hite Paper B ']);"
      t44u User & Partner Conference 2010
    • 8. Step 3 – The Variations Pages (media formatter code)
      • Updated media formatter (so it can have an onclick attribute):
        • <a href=&quot;<t4 type=&quot;content&quot; output=&quot;file&quot; modifiers=&quot;nav_sections&quot; name=&quot;Media&quot; />&quot; title=&quot;<t4 type=&quot;content&quot; output=&quot;normal&quot; modifiers=&quot;nav_sections&quot; name=&quot;Description&quot; />&quot; <t4 type=&quot;media&quot; attribute=&quot;onClick&quot; format=&quot;onClick=&quot;$value&quot;&quot; /> target=&quot;_blank&quot;><t4 type=&quot;content&quot; name=&quot;Name&quot; output=&quot;normal&quot; modifiers=&quot;&quot; /></a>
      t44u User & Partner Conference 2010
    • 9. Step 4 - Measuring
      • In the Google Analytics interface, results can be seen under Content > Event Tracking:
      t44u User & Partner Conference 2010
    • 10. Conclusion
      • A/B testing can also be used to test variations in colour, copy or any element of the page layout.
      • A/B testing is more efficient if you test single-variable variations rather than variations of multiple variables.
      • Note that what we have demonstrated is just one of many possible methods that can be used. Just Google “A/B testing tools” 
      t44u User & Partner Conference 2010

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