I was recently asked whether I wanted to answer a set of questions in line with the topic of my blog – which I am of course delighted to do. The first question goes like this:

Q. Ingrid:
“Kindly give us an example of when analytics could increase an affiliates revenue drastically – indicating why analytics was important and how it was used”

A. Dennis:
No problem Ingrid. First, let me point out that I think there is multiple Analytics Strategies that an Affiliate (on any level) can use to increase revenue, but to answer your question on a very actionable level, I will use one of my favourite affiliate metrics as an example; The “Conversion Participation Metric”. (I talked a bit about conversion funnels on my blog last month, and this is what I described as a “Non-Linear Path towards conversion”).
Most affiliates (or Publisher as some call it) write valuable content that are aligned with their keyword strategy and use these pages as part of their SEO (Search Engine Optimization) strategy. However; ranking well and driving in organic traffic on a specific set of keywords, based on a well optimized content page, is not the same as concluding that this is the page that contributes the most towards conversion.

Conversion of course being a bit tricky when you are an affiliate (I briefly touched the subject in my outline of conversion tracking for affiliates post). Complicated because you typically do not convert the visitor on your own site, this is done on the retailers site. But let’s just conclude for the sake of the example that conversion is a “On Click conversion” (clicking the retailers banner). As an example, let’s imagine an affiliate website with the following pages:

• CarPage01.html
• CarPage02.html
• CarPage03.html
• CarPage04.html
• …
• CarPage99.html

Best performing affiliate programs for this imaginary website is:

• TradeDoubler’s “AVIS Car Rental”
• TradeDoubler’s “Hertz Car Rental”

The content pages all drive relevant incoming traffic for wanted keywords, BUT given the question on how to optimize your content to increase “Car Rental” conversion (clicks on banners) – we simply do not know which of our pages contributes the most towards this conversion. So we would not be able to conclude where to optimize. This is where the Web Analytics Conversion Participation Metrics comes in handy. Running a report on the pages that contributed the most towards the “Car Rental” conversions, we would be able to find out that it is in fact e.g. CarPage37.html and 5 other pages that contributes the most when talking about these conversions (Remember we might even find pages here that do NOT have the AVIS or Hertz banners). This conclusion gives us a clear actionable insight of where to optimize for even better conversions in the future, it might even enlighten us on what behaviour drives “Car Rental” conversion.

I hope this straight forward example gives you and your readers an indication of how powerful analytics can be. :-)

Go see the original post here: http://www.rabbitblog.hu/2007/03/13/webanalitika-novekvo-bevetel (Hungarian)