Combining Statistics, SiteCatalyst, and Test&Target for Massive Conversion Lift

- Trevor Paulsen

Both SiteCatalyst and Test&Target are amazing and powerful tools that allow a digital marketer to better understand the traffic on their site and test their marketing ideas among groups of users.  However, business users often wonder how to make sense of the titanic amount of data that is collected and actually use it to increase conversion on their site.  What I’m going to show you today is that you can actually build a statistical model to find the users who are most likely to complete a conversion using SiteCatalyst, and then target those exact individuals using Test&Target to really get some amazing conversion lift!

To explain how this works, let me break the process down into the following steps that I’ll explain in more detail:

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Read the full blog post at Adobe Digital Marketing Blog.

Using SiteCatalyst to Build Media Mix Models

- Trevor Paulsen

Adobe’s Digital Marketing solutions are now opening doors to predictive marketing optimizations that were previously only available to huge companies that spend millions of dollars constructing complex economic models to explain the reach of their marketing spend.  These large models typically include surveys, studies, panels, and hosts of other expensive outside resources to deliver statistical optimization to your marketing budget that will maximize your return on spend.

With Adobe’s recent acquisition of Efficient Frontier and recent advancements in predictive consulting, SiteCatalyst customers are able to unleash the full potential of their web analytics data in ways that have not been possible before.

One particular customer Adobe Consulting recently engaged with wanted to determine how to best allocate their digital marketing budget based on several years of historical performance.  Their digital marketing channels included SEO, SEM, affiliates, media advertising, social media, network partners, and email campaigns.  Because the performance of these channels had been thoroughly recorded across several years, Adobe Consulting was able to use this data to form statistical performance models around each of these marketing channels.

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Read the full blog post at Adobe Digital Marketing Blog.

Unleashing the Full Power of eVar Subrelations

- Trevor Paulsen

Time and time again I’m amazed by the power that a subrelated eVar report can provide.  Believe it or not, if you’re clever (as you will be after reading this), you can actually use Adobe Report Builder to find interesting data anomalies for you!  First of all, if you’re not familiar with what an eVar subrelation is, let me explain:

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Read the full blog post at Adobe Digital Marketing Blog.

Using Predictive Analytics to Create Business Intelligence Masterpieces

- Trevor Paulsen

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It is hard to believe that both of these paint­ings were cre­ated by the same artist.  At left, Picasso’s The Old Fish­er­man, dis­plays amaz­ing detail and depth of knowl­edge about the human fig­ure.  At right, Three Musi­cians, presents amaz­ing con­trast and is so sim­ple that it almost seems like any­one could have painted it with­out any train­ing at all, and yet it is the more well-known of the two.  I have often won­dered why that is.

Believe it or not, there is a strong tie in here with web ana­lyt­ics.  The rea­son that the sec­ond image is more pow­er­ful is not because of its sur­face appear­ance; it is the depth of knowl­edge of the artist behind it.

Recently one of our largest media clients asked the Adobe con­sult­ing team to help them iden­tify four to five key user mar­ket seg­ments using pre­dic­tive ana­lyt­ics and the data cap­tured by Site­Cat­a­lyst.  This was an extremely chal­leng­ing task con­sid­er­ing the client has over 80 mil­lion unique vis­i­tors to their site each month, each with unique behav­ior and con­tent affini­ties across many indi­vid­ual vis­its.  It was our task to char­ac­ter­ize each indi­vid­ual user, and then find a way to group these users into use­ful and action­able seg­ments that could be used by the client’s mar­ket­ing team to hone their efforts.

We started by iden­ti­fy­ing the Site­Cat­a­lyst met­rics that were most impor­tant to our client’s rev­enue stream.  Most of these met­rics cen­tered on video mea­sure­ment but we also incor­po­rated visit infor­ma­tion (length of visit, entry time, entry page, etc.), refer­rer infor­ma­tion (includ­ing search key­words), and geo­graphic loca­tion.  We then cre­ated an algo­rithm that could take all avail­able infor­ma­tion from each user and cre­ate a series of user pro­files to which each indi­vid­ual vis­i­tor belongs.

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Read the complete post at the Adobe Digital Marketing blog.